GPUTPCGMMerger.cxx

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// Copyright 2019-2020 CERN and copyright holders of ALICE O2.
// See https://alice-o2.web.cern.ch/copyright for details of the copyright holders.
// All rights not expressly granted are reserved.
//
// This software is distributed under the terms of the GNU General Public
// License v3 (GPL Version 3), copied verbatim in the file "COPYING".
//
// In applying this license CERN does not waive the privileges and immunities
// granted to it by virtue of its status as an Intergovernmental Organization
// or submit itself to any jurisdiction.
 
 
#define GPUCA_CADEBUG 0
#define GPUCA_MERGE_LOOPER_MC 0
 
#include "GPUCommonDef.h"
 
#if !defined(GPUCA_GPUCODE) && (defined(GPUCA_MERGER_BY_MC_LABEL) || defined(GPUCA_CADEBUG_ENABLED) || GPUCA_MERGE_LOOPER_MC)
#include "AliHLTTPCClusterMCData.h"
#include "GPUROOTDump.h"
#endif
 
#ifndef GPUCA_GPUCODE_DEVICE
#include <cstdio>
#include <cstring>
#include <cmath>
#include "GPUReconstruction.h"
#endif
 
#include "GPUTPCTracker.h"
#include "GPUTPCClusterData.h"
#include "GPUTPCTrackParam.h"
#include "GPUTPCGMMerger.h"
#include "GPUO2DataTypes.h"
#include "TPCFastTransform.h"
#include "GPUTPCConvertImpl.h"
#include "GPUTPCGeometry.h"
#include "GPUDefParametersRuntime.h"
 
#include "GPUCommonMath.h"
#include "GPUCommonAlgorithm.h"
#include "GPUCommonConstants.h"
 
#include "GPUTPCTrackParam.h"
#include "GPUTPCGMMergedTrack.h"
#include "GPUParam.h"
#include "GPUTPCTrackLinearisation.h"
 
#include "GPUTPCGMTrackParam.h"
#include "GPUTPCGMSectorTrack.h"
#include "GPUTPCGMBorderTrack.h"
 
#include "DataFormatsTPC/ClusterNative.h"
#include "DataFormatsTPC/TrackTPC.h"
#ifndef GPUCA_GPUCODE
#include "SimulationDataFormat/ConstMCTruthContainer.h"
#include "SimulationDataFormat/MCCompLabel.h"
#endif
 
namespace o2::gpu::internal
{
}
using namespace o2::gpu;
using namespace o2::gpu::internal;
using namespace o2::tpc;
using namespace gputpcgmmergertypes;
 
static constexpr int32_t kMaxParts = 400;
static constexpr int32_t kMaxClusters = GPUCA_MERGER_MAX_TRACK_CLUSTERS;
 
namespace o2::gpu::internal
{
struct MergeLooperParam {
  float refz;
  float x;
  float y;
  uint32_t id;
};
} // namespace o2::gpu::internal
 
#ifndef GPUCA_GPUCODE
 
#include "GPUQA.h"
#include "GPUMemorySizeScalers.h"
 
GPUTPCGMMerger::GPUTPCGMMerger()
{
  for (int32_t iSector = 0; iSector < NSECTORS; iSector++) {
    mNextSectorInd[iSector] = iSector + 1;
    mPrevSectorInd[iSector] = iSector - 1;
  }
  int32_t mid = NSECTORS / 2 - 1;
  int32_t last = NSECTORS - 1;
  mNextSectorInd[mid] = 0;
  mPrevSectorInd[0] = mid;
  mNextSectorInd[last] = NSECTORS / 2;
  mPrevSectorInd[NSECTORS / 2] = last;
}
 
// DEBUG CODE
#if !defined(GPUCA_GPUCODE) && (defined(GPUCA_MERGER_BY_MC_LABEL) || defined(GPUCA_CADEBUG_ENABLED) || GPUCA_MERGE_LOOPER_MC)
#include "GPUQAHelper.h"
 
void GPUTPCGMMerger::CheckMergedTracks()
{
  std::vector<bool> trkUsed(SectorTrackInfoLocalTotal());
  for (int32_t i = 0; i < SectorTrackInfoLocalTotal(); i++) {
    trkUsed[i] = false;
  }
 
  for (int32_t itr = 0; itr < SectorTrackInfoLocalTotal(); itr++) {
    GPUTPCGMSectorTrack& track = mSectorTrackInfos[itr];
    if (track.PrevSegmentNeighbour() >= 0) {
      continue;
    }
    if (track.PrevNeighbour() >= 0) {
      continue;
    }
    int32_t leg = 0;
    GPUTPCGMSectorTrack *trbase = &track, *tr = &track;
    while (true) {
      int32_t iTrk = tr - mSectorTrackInfos;
      if (trkUsed[iTrk]) {
        GPUError("FAILURE: double use");
      }
      trkUsed[iTrk] = true;
 
      int32_t jtr = tr->NextSegmentNeighbour();
      if (jtr >= 0) {
        tr = &(mSectorTrackInfos[jtr]);
        continue;
      }
      jtr = trbase->NextNeighbour();
      if (jtr >= 0) {
        trbase = &(mSectorTrackInfos[jtr]);
        tr = trbase;
        if (tr->PrevSegmentNeighbour() >= 0) {
          break;
        }
        leg++;
        continue;
      }
      break;
    }
  }
  for (int32_t i = 0; i < SectorTrackInfoLocalTotal(); i++) {
    if (trkUsed[i] == false) {
      GPUError("FAILURE: trk missed");
    }
  }
}
 
template <class T>
inline const auto* resolveMCLabels(const o2::dataformats::ConstMCTruthContainerView<o2::MCCompLabel>* a, const AliHLTTPCClusterMCLabel* b)
{
  return a;
}
template <>
inline const auto* resolveMCLabels<AliHLTTPCClusterMCLabel>(const o2::dataformats::ConstMCTruthContainerView<o2::MCCompLabel>* a, const AliHLTTPCClusterMCLabel* b)
{
  return b;
}
 
template <class T, class S>
int64_t GPUTPCGMMerger::GetTrackLabelA(const S& trk) const
{
  GPUTPCGMSectorTrack* sectorTrack = nullptr;
  int32_t nClusters = 0;
  if constexpr (std::is_same<S, GPUTPCGMBorderTrack&>::value) {
    sectorTrack = &mSectorTrackInfos[trk.TrackID()];
    nClusters = sectorTrack->OrigTrack()->NHits();
  } else {
    nClusters = trk.NClusters();
  }
  auto acc = GPUTPCTrkLbl<false, GPUTPCTrkLbl_ret>(resolveMCLabels<T>(GetConstantMem()->ioPtrs.clustersNative ? GetConstantMem()->ioPtrs.clustersNative->clustersMCTruth : nullptr, GetConstantMem()->ioPtrs.mcLabelsTPC), 0.5f);
  for (int32_t i = 0; i < nClusters; i++) {
    int32_t id;
    if constexpr (std::is_same<S, GPUTPCGMBorderTrack&>::value) {
      const GPUTPCTracker& tracker = GetConstantMem()->tpcTrackers[sectorTrack->Sector()];
      const GPUTPCHitId& ic = tracker.TrackHits()[sectorTrack->OrigTrack()->FirstHitID() + i];
      id = tracker.Data().ClusterDataIndex(tracker.Data().Row(ic.RowIndex()), ic.HitIndex()) + GetConstantMem()->ioPtrs.clustersNative->clusterOffset[sectorTrack->Sector()][0];
    } else {
      id = mClusters[trk.FirstClusterRef() + i].num;
    }
    acc.addLabel(id);
  }
  return acc.computeLabel().id;
}
 
template <class S>
int64_t GPUTPCGMMerger::GetTrackLabel(const S& trk) const
{
#ifdef GPUCA_TPC_GEOMETRY_O2
  if (GetConstantMem()->ioPtrs.clustersNative->clustersMCTruth) {
    return GetTrackLabelA<o2::dataformats::ConstMCTruthContainerView<o2::MCCompLabel>, S>(trk);
  } else
#endif
  {
    return GetTrackLabelA<AliHLTTPCClusterMCLabel, S>(trk);
  }
}
 
#endif
// END DEBUG CODE
 
void GPUTPCGMMerger::PrintMergeGraph(const GPUTPCGMSectorTrack* trk, std::ostream& out) const
{
  const GPUTPCGMSectorTrack* orgTrack = trk;
  while (trk->PrevSegmentNeighbour() >= 0) {
    trk = &mSectorTrackInfos[trk->PrevSegmentNeighbour()];
  }
  const GPUTPCGMSectorTrack* orgTower = trk;
  while (trk->PrevNeighbour() >= 0) {
    trk = &mSectorTrackInfos[trk->PrevNeighbour()];
  }
 
  int32_t nextId = trk - mSectorTrackInfos;
  out << "Graph of track " << (orgTrack - mSectorTrackInfos) << "\n";
  while (nextId >= 0) {
    trk = &mSectorTrackInfos[nextId];
    if (trk->PrevSegmentNeighbour() >= 0) {
      out << "TRACK TREE INVALID!!! " << trk->PrevSegmentNeighbour() << " --> " << nextId << "\n";
    }
    out << (trk == orgTower ? "--" : "  ");
    while (nextId >= 0) {
      GPUTPCGMSectorTrack* trk2 = &mSectorTrackInfos[nextId];
      if (trk != trk2 && (trk2->PrevNeighbour() >= 0 || trk2->NextNeighbour() >= 0)) {
        out << "   (TRACK TREE INVALID!!! " << trk2->PrevNeighbour() << " <-- " << nextId << " --> " << trk2->NextNeighbour() << ")   ";
      }
      char tmp[128];
      snprintf(tmp, 128, " %s%5d(%5.2f)", trk2 == orgTrack ? "!" : " ", nextId, trk2->QPt());
      out << tmp;
      nextId = trk2->NextSegmentNeighbour();
    }
    out << "\n";
    nextId = trk->NextNeighbour();
  }
}
 
void GPUTPCGMMerger::InitializeProcessor() {}
 
void* GPUTPCGMMerger::SetPointersMerger(void* mem)
{
  computePointerWithAlignment(mem, mSectorTrackInfos, mNTotalSectorTracks);
  computePointerWithAlignment(mem, mSectorTrackInfoIndex, NSECTORS * 2 + 1);
  if (mRec->GetProcessingSettings().deterministicGPUReconstruction) {
    computePointerWithAlignment(mem, mTmpSortMemory, std::max(mNTotalSectorTracks, mNMaxTracks * 2));
  }
 
  void* memBase = mem;
  computePointerWithAlignment(mem, mBorderMemory, 2 * mNTotalSectorTracks); // MergeBorders & Resolve
  computePointerWithAlignment(mem, mBorderRangeMemory, 2 * mNTotalSectorTracks);
  int32_t nTracks = 0;
  for (int32_t iSector = 0; iSector < NSECTORS; iSector++) {
    const int32_t n = *mRec->GetConstantMem().tpcTrackers[iSector].NTracks();
    mBorder[iSector] = mBorderMemory + 2 * nTracks;
    mBorder[NSECTORS + iSector] = mBorderMemory + 2 * nTracks + n;
    mBorderRange[iSector] = mBorderRangeMemory + 2 * nTracks;
    nTracks += n;
  }
  computePointerWithAlignment(mem, mTrackLinks, mNTotalSectorTracks);
  computePointerWithAlignment(mem, mTrackCCRoots, mNTotalSectorTracks);
  void* memMax = mem;
  mem = memBase;
  computePointerWithAlignment(mem, mTrackIDs, GPUCA_NSECTORS * mNMaxSingleSectorTracks); // UnpackResetIds - RefitSectorTracks - UnpackSectorGlobal
  memMax = (void*)std::max((size_t)mem, (size_t)memMax);
  mem = memBase;
  computePointerWithAlignment(mem, mTrackSort, mNMaxTracks); // PrepareClustersForFit0 - SortTracksQPt - PrepareClustersForFit1 - PrepareClustersForFit1 / Finalize0 - Finalize2
  computePointerWithAlignment(mem, mSharedCount, mNMaxClusters);
  memMax = (void*)std::max((size_t)mem, (size_t)memMax);
  mem = memBase;
  computePointerWithAlignment(mem, mLoopData, mNMaxTracks);      // GPUTPCGMMergerTrackFit - GPUTPCGMMergerFollowLoopers
  computePointerWithAlignment(mem, mRetryRefitIds, mNMaxTracks); // Reducing mNMaxTracks for mLoopData / mRetryRefitIds does not save memory, since the other parts are larger anyway
  memMax = (void*)std::max((size_t)mem, (size_t)memMax);
  mem = memBase;
  computePointerWithAlignment(mem, mLooperCandidates, mNMaxLooperMatches); // MergeLoopers 1-3
  memMax = (void*)std::max((size_t)mem, (size_t)memMax);
  return memMax;
}
 
void* GPUTPCGMMerger::SetPointersMemory(void* mem)
{
  computePointerWithAlignment(mem, mMemory);
  return mem;
}
 
void* GPUTPCGMMerger::SetPointersRefitScratch(void* mem)
{
  computePointerWithAlignment(mem, mTrackOrderAttach, mNMaxTracks);
  const bool mergerSortTracks = mRec->GetProcessingSettings().mergerSortTracks == -1 ? mRec->getGPUParameters(mRec->GetRecoStepsGPU() & GPUDataTypes::RecoStep::TPCMerging).par_SORT_BEFORE_FIT : mRec->GetProcessingSettings().mergerSortTracks;
  if (mergerSortTracks) {
    computePointerWithAlignment(mem, mTrackOrderProcess, mNMaxTracks);
  }
  return mem;
}
 
void* GPUTPCGMMerger::SetPointersOutput(void* mem)
{
  computePointerWithAlignment(mem, mOutputTracks, mNMaxTracks);
  if (mRec->GetParam().dodEdxDownscaled) {
    computePointerWithAlignment(mem, mOutputTracksdEdx, mNMaxTracks);
    computePointerWithAlignment(mem, mOutputTracksdEdxAlt, mNMaxTracks);
  }
  computePointerWithAlignment(mem, mClusters, mNMaxOutputTrackClusters);
  if (mRec->GetParam().par.earlyTpcTransform) {
    computePointerWithAlignment(mem, mClustersXYZ, mNMaxOutputTrackClusters);
  }
  computePointerWithAlignment(mem, mClusterAttachment, mNMaxClusters);
  return mem;
}
 
void* GPUTPCGMMerger::SetPointersOutputState(void* mem)
{
  if ((mRec->GetRecoSteps() & GPUDataTypes::RecoStep::Refit) || mRec->GetProcessingSettings().outputSharedClusterMap) {
    computePointerWithAlignment(mem, mClusterStateExt, mNMaxClusters);
  } else {
    mClusterStateExt = nullptr;
  }
  return mem;
}
 
void* GPUTPCGMMerger::SetPointersOutputO2(void* mem)
{
  computePointerWithAlignment(mem, mOutputTracksTPCO2, HostProcessor(this).NOutputTracksTPCO2());
  return mem;
}
 
void* GPUTPCGMMerger::SetPointersOutputO2Clus(void* mem)
{
  computePointerWithAlignment(mem, mOutputClusRefsTPCO2, HostProcessor(this).NOutputClusRefsTPCO2());
  return mem;
}
 
void* GPUTPCGMMerger::SetPointersOutputO2MC(void* mem)
{
  computePointerWithAlignment(mem, mOutputTracksTPCO2MC, HostProcessor(this).NOutputTracksTPCO2());
  return mem;
}
 
void* GPUTPCGMMerger::SetPointersOutputO2Scratch(void* mem)
{
  computePointerWithAlignment(mem, mTrackSortO2, mNMaxTracks);
  computePointerWithAlignment(mem, mClusRefTmp, mNMaxTracks);
  return mem;
}
 
void GPUTPCGMMerger::RegisterMemoryAllocation()
{
  AllocateAndInitializeLate();
  mRec->RegisterMemoryAllocation(this, &GPUTPCGMMerger::SetPointersMerger, GPUMemoryResource::MEMORY_SCRATCH | GPUMemoryResource::MEMORY_STACK, "TPCMerger");
  mRec->RegisterMemoryAllocation(this, &GPUTPCGMMerger::SetPointersRefitScratch, GPUMemoryResource::MEMORY_SCRATCH | GPUMemoryResource::MEMORY_STACK, "TPCMergerRefitScratch");
  mMemoryResOutput = mRec->RegisterMemoryAllocation(this, &GPUTPCGMMerger::SetPointersOutput, (mRec->GetProcessingSettings().createO2Output > 1 ? GPUMemoryResource::MEMORY_SCRATCH : GPUMemoryResource::MEMORY_OUTPUT) | GPUMemoryResource::MEMORY_CUSTOM, "TPCMergerOutput");
  mMemoryResOutputState = mRec->RegisterMemoryAllocation(this, &GPUTPCGMMerger::SetPointersOutputState, (mRec->GetProcessingSettings().outputSharedClusterMap ? GPUMemoryResource::MEMORY_OUTPUT : GPUMemoryResource::MEMORY_GPU) | GPUMemoryResource::MEMORY_CUSTOM, "TPCMergerOutputState");
  if (mRec->GetProcessingSettings().createO2Output) {
    mMemoryResOutputO2Scratch = mRec->RegisterMemoryAllocation(this, &GPUTPCGMMerger::SetPointersOutputO2Scratch, GPUMemoryResource::MEMORY_SCRATCH | GPUMemoryResource::MEMORY_STACK | GPUMemoryResource::MEMORY_CUSTOM, "TPCMergerOutputO2Scratch");
    mMemoryResOutputO2 = mRec->RegisterMemoryAllocation(this, &GPUTPCGMMerger::SetPointersOutputO2, GPUMemoryResource::MEMORY_OUTPUT | GPUMemoryResource::MEMORY_CUSTOM, "TPCMergerOutputO2");
    mMemoryResOutputO2Clus = mRec->RegisterMemoryAllocation(this, &GPUTPCGMMerger::SetPointersOutputO2Clus, GPUMemoryResource::MEMORY_OUTPUT | GPUMemoryResource::MEMORY_CUSTOM, "TPCMergerOutputO2Clus");
    if (mRec->GetProcessingSettings().runMC) {
      mMemoryResOutputO2MC = mRec->RegisterMemoryAllocation(this, &GPUTPCGMMerger::SetPointersOutputO2MC, GPUMemoryResource::MEMORY_OUTPUT_FLAG | GPUMemoryResource::MEMORY_HOST | GPUMemoryResource::MEMORY_CUSTOM, "TPCMergerOutputO2MC");
    }
  }
  mMemoryResMemory = mRec->RegisterMemoryAllocation(this, &GPUTPCGMMerger::SetPointersMemory, GPUMemoryResource::MEMORY_PERMANENT, "TPCMergerMemory");
}
 
void GPUTPCGMMerger::SetMaxData(const GPUTrackingInOutPointers& io)
{
  mNTotalSectorTracks = 0;
  mNClusters = 0;
  mNMaxSingleSectorTracks = 0;
  for (int32_t iSector = 0; iSector < NSECTORS; iSector++) {
    uint32_t ntrk = *mRec->GetConstantMem().tpcTrackers[iSector].NTracks();
    mNTotalSectorTracks += ntrk;
    mNClusters += *mRec->GetConstantMem().tpcTrackers[iSector].NTrackHits();
    if (mNMaxSingleSectorTracks < ntrk) {
      mNMaxSingleSectorTracks = ntrk;
    }
  }
  mNMaxOutputTrackClusters = mRec->MemoryScalers()->NTPCMergedTrackHits(mNClusters);
  if (CAMath::Abs(Param().polynomialField.GetNominalBz()) < (gpu_common_constants::kZeroFieldCut * gpu_common_constants::kCLight)) {
    mNMaxTracks = mRec->MemoryScalers()->getValue(mNTotalSectorTracks, mNTotalSectorTracks); // 0 magnetic field
  } else {
    mNMaxTracks = mRec->MemoryScalers()->NTPCMergedTracks(mNTotalSectorTracks);
  }
  if (io.clustersNative) {
    mNMaxClusters = io.clustersNative->nClustersTotal;
  } else if (mRec->GetRecoSteps() & GPUDataTypes::RecoStep::TPCSectorTracking) {
    mNMaxClusters = 0;
    for (int32_t i = 0; i < NSECTORS; i++) {
      mNMaxClusters += mRec->GetConstantMem().tpcTrackers[i].NHitsTotal();
    }
  } else {
    mNMaxClusters = mNClusters;
  }
  mNMaxLooperMatches = mNMaxClusters / 4; // We have that much scratch memory anyway
}
 
int32_t GPUTPCGMMerger::CheckSectors()
{
  for (int32_t i = 0; i < NSECTORS; i++) {
    if (mRec->GetConstantMem().tpcTrackers[i].CommonMemory()->nLocalTracks > (int32_t)mNMaxSingleSectorTracks) {
      throw std::runtime_error("mNMaxSingleSectorTracks too small");
    }
  }
  if (!(mRec->GetRecoSteps() & GPUDataTypes::RecoStep::TPCSectorTracking)) {
    throw std::runtime_error("Must run also sector tracking");
  }
  return 0;
}
 
#endif // GPUCA_GPUCODE
 
GPUd() void GPUTPCGMMerger::ClearTrackLinks(int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread, bool output)
{
  const int32_t n = output ? mMemory->nOutputTracks : SectorTrackInfoLocalTotal();
  for (int32_t i = iBlock * nThreads + iThread; i < n; i += nThreads * nBlocks) {
    mTrackLinks[i] = -1;
  }
}
 
GPUd() int32_t GPUTPCGMMerger::RefitSectorTrack(GPUTPCGMSectorTrack& sectorTrack, const GPUTPCTrack* inTrack, float alpha, int32_t sector)
{
  GPUTPCGMPropagator prop;
  prop.SetMaterialTPC();
  prop.SetMaxSinPhi(GPUCA_MAX_SIN_PHI);
  prop.SetToyMCEventsFlag(false);
  prop.SetSeedingErrors(true); // Larger errors for seeds, better since we don't start with good hypothesis
  prop.SetFitInProjections(false);
  prop.SetPolynomialField(&Param().polynomialField);
  GPUTPCGMTrackParam trk;
  trk.X() = inTrack->Param().GetX();
  trk.Y() = inTrack->Param().GetY();
  trk.Z() = inTrack->Param().GetZ();
  trk.SinPhi() = inTrack->Param().GetSinPhi();
  trk.DzDs() = inTrack->Param().GetDzDs();
  trk.QPt() = inTrack->Param().GetQPt();
  trk.TZOffset() = Param().par.earlyTpcTransform ? inTrack->Param().GetZOffset() : GetConstantMem()->calibObjects.fastTransformHelper->getCorrMap()->convZOffsetToVertexTime(sector, inTrack->Param().GetZOffset(), Param().continuousMaxTimeBin);
  trk.ShiftZ(this, sector, sectorTrack.ClusterZT0(), sectorTrack.ClusterZTN(), inTrack->Param().GetX(), inTrack->Param().GetX()); // We do not store the inner / outer cluster X, so we just use the track X instead
  sectorTrack.SetX2(0.f);
  for (int32_t way = 0; way < 2; way++) {
    if (way) {
      prop.SetFitInProjections(true);
      prop.SetPropagateBzOnly(true);
    }
    trk.ResetCovariance();
    prop.SetTrack(&trk, alpha);
    int32_t start = way ? inTrack->NHits() - 1 : 0;
    int32_t end = way ? 0 : (inTrack->NHits() - 1);
    int32_t incr = way ? -1 : 1;
    for (int32_t i = start; i != end; i += incr) {
      float x, y, z;
      int32_t row, flags;
      const GPUTPCTracker& tracker = GetConstantMem()->tpcTrackers[sector];
      const GPUTPCHitId& ic = tracker.TrackHits()[inTrack->FirstHitID() + i];
      int32_t clusterIndex = tracker.Data().ClusterDataIndex(tracker.Data().Row(ic.RowIndex()), ic.HitIndex());
      row = ic.RowIndex();
      const ClusterNative& cl = GetConstantMem()->ioPtrs.clustersNative->clustersLinear[GetConstantMem()->ioPtrs.clustersNative->clusterOffset[sector][0] + clusterIndex];
      flags = cl.getFlags();
      if (Param().par.earlyTpcTransform) {
        x = tracker.Data().ClusterData()[clusterIndex].x;
        y = tracker.Data().ClusterData()[clusterIndex].y;
        z = tracker.Data().ClusterData()[clusterIndex].z - trk.TZOffset();
      } else {
        GetConstantMem()->calibObjects.fastTransformHelper->Transform(sector, row, cl.getPad(), cl.getTime(), x, y, z, trk.TZOffset());
      }
      if (prop.PropagateToXAlpha(x, alpha, true)) {
        return way == 0;
      }
      trk.ConstrainSinPhi();
      if (prop.Update(y, z, row, Param(), flags & GPUTPCGMMergedTrackHit::clustererAndSharedFlags, 0, nullptr, false, sector, -1.f, 0.f, 0.f)) { // TODO: Use correct time / avgCharge
        return way == 0;
      }
      trk.ConstrainSinPhi();
    }
    if (way) {
      sectorTrack.SetParam2(trk);
    } else {
      sectorTrack.Set(trk, inTrack, alpha, sector);
    }
  }
  return 0;
}
 
GPUd() void GPUTPCGMMerger::SetTrackClusterZT(GPUTPCGMSectorTrack& track, int32_t iSector, const GPUTPCTrack* sectorTr)
{
  const GPUTPCTracker& trk = GetConstantMem()->tpcTrackers[iSector];
  const GPUTPCHitId& ic1 = trk.TrackHits()[sectorTr->FirstHitID()];
  const GPUTPCHitId& ic2 = trk.TrackHits()[sectorTr->FirstHitID() + sectorTr->NHits() - 1];
  int32_t clusterIndex1 = trk.Data().ClusterDataIndex(trk.Data().Row(ic1.RowIndex()), ic1.HitIndex());
  int32_t clusterIndex2 = trk.Data().ClusterDataIndex(trk.Data().Row(ic2.RowIndex()), ic2.HitIndex());
  if (Param().par.earlyTpcTransform) {
    track.SetClusterZT(trk.Data().ClusterData()[clusterIndex1].z, trk.Data().ClusterData()[clusterIndex2].z);
  } else {
    const ClusterNative* cl = GetConstantMem()->ioPtrs.clustersNative->clustersLinear + GetConstantMem()->ioPtrs.clustersNative->clusterOffset[iSector][0];
    track.SetClusterZT(cl[clusterIndex1].getTime(), cl[clusterIndex2].getTime());
  }
}
 
GPUd() void GPUTPCGMMerger::UnpackSaveNumber(int32_t id)
{
  mSectorTrackInfoIndex[id] = mMemory->nUnpackedTracks;
}
 
GPUd() void GPUTPCGMMerger::UnpackSectorGlobal(int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread, int32_t iSector)
{
  const GPUTPCTracker& trk = GetConstantMem()->tpcTrackers[iSector];
  float alpha = Param().Alpha(iSector);
  const GPUTPCTrack* sectorTr = mMemory->firstExtrapolatedTracks[iSector];
  uint32_t nLocalTracks = trk.CommonMemory()->nLocalTracks;
  uint32_t nTracks = *trk.NTracks();
  for (uint32_t itr = nLocalTracks + iBlock * nThreads + iThread; itr < nTracks; itr += nBlocks * nThreads) {
    sectorTr = &trk.Tracks()[itr];
    int32_t localId = mTrackIDs[(sectorTr->LocalTrackId() >> 24) * mNMaxSingleSectorTracks + (sectorTr->LocalTrackId() & 0xFFFFFF)];
    if (localId == -1) {
      continue;
    }
    uint32_t myTrack = CAMath::AtomicAdd(&mMemory->nUnpackedTracks, 1u);
    GPUTPCGMSectorTrack& track = mSectorTrackInfos[myTrack];
    SetTrackClusterZT(track, iSector, sectorTr);
    track.Set(this, sectorTr, alpha, iSector);
    track.SetGlobalSectorTrackCov();
    track.SetPrevNeighbour(-1);
    track.SetNextNeighbour(-1);
    track.SetNextSegmentNeighbour(-1);
    track.SetPrevSegmentNeighbour(-1);
    track.SetLocalTrackId(localId);
  }
}
 
GPUd() void GPUTPCGMMerger::UnpackResetIds(int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread, int32_t iSector)
{
  const GPUTPCTracker& trk = GetConstantMem()->tpcTrackers[iSector];
  uint32_t nLocalTracks = trk.CommonMemory()->nLocalTracks;
  for (uint32_t i = iBlock * nThreads + iThread; i < nLocalTracks; i += nBlocks * nThreads) {
    mTrackIDs[iSector * mNMaxSingleSectorTracks + i] = -1;
  }
}
 
GPUd() void GPUTPCGMMerger::RefitSectorTracks(int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread, int32_t iSector)
{
  const GPUTPCTracker& trk = GetConstantMem()->tpcTrackers[iSector];
  uint32_t nLocalTracks = trk.CommonMemory()->nLocalTracks;
 
  float alpha = Param().Alpha(iSector);
  const GPUTPCTrack* sectorTr = nullptr;
 
  for (uint32_t itr = iBlock * nThreads + iThread; itr < nLocalTracks; itr += nBlocks * nThreads) {
    sectorTr = &trk.Tracks()[itr];
    GPUTPCGMSectorTrack track;
    SetTrackClusterZT(track, iSector, sectorTr);
    if (Param().rec.tpc.mergerCovSource == 0) {
      track.Set(this, sectorTr, alpha, iSector);
      if (!track.FilterErrors(this, iSector, GPUCA_MAX_SIN_PHI, 0.1f)) {
        continue;
      }
    } else if (Param().rec.tpc.mergerCovSource == 1) {
      track.Set(this, sectorTr, alpha, iSector);
      track.CopyBaseTrackCov();
    } else if (Param().rec.tpc.mergerCovSource == 2) {
      if (RefitSectorTrack(track, sectorTr, alpha, iSector)) {
        track.Set(this, sectorTr, alpha, iSector); // TODO: Why does the refit fail, it shouldn't, this workaround should be removed
        if (!track.FilterErrors(this, iSector, GPUCA_MAX_SIN_PHI, 0.1f)) {
          continue;
        }
      }
    }
 
    CADEBUG(GPUInfo("INPUT Sector %d, Track %u, QPt %f DzDs %f", iSector, itr, track.QPt(), track.DzDs()));
    track.SetPrevNeighbour(-1);
    track.SetNextNeighbour(-1);
    track.SetNextSegmentNeighbour(-1);
    track.SetPrevSegmentNeighbour(-1);
    track.SetExtrapolatedTrackId(0, -1);
    track.SetExtrapolatedTrackId(1, -1);
    uint32_t myTrack = CAMath::AtomicAdd(&mMemory->nUnpackedTracks, 1u);
    mTrackIDs[iSector * mNMaxSingleSectorTracks + sectorTr->LocalTrackId()] = myTrack;
    mSectorTrackInfos[myTrack] = track;
  }
}
 
GPUd() void GPUTPCGMMerger::LinkExtrapolatedTracks(int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread)
{
  for (int32_t itr = SectorTrackInfoGlobalFirst(0) + iBlock * nThreads + iThread; itr < SectorTrackInfoGlobalLast(NSECTORS - 1); itr += nThreads * nBlocks) {
    GPUTPCGMSectorTrack& extrapolatedTrack = mSectorTrackInfos[itr];
    GPUTPCGMSectorTrack& localTrack = mSectorTrackInfos[extrapolatedTrack.LocalTrackId()];
    if (localTrack.ExtrapolatedTrackId(0) != -1 || !CAMath::AtomicCAS(&localTrack.ExtrapolatedTrackIds()[0], -1, itr)) {
      localTrack.SetExtrapolatedTrackId(1, itr);
    }
  }
}
 
GPUd() void GPUTPCGMMerger::MergeSectorsPrepareStep2(int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread, int32_t iBorder, GPUTPCGMBorderTrack** B, GPUAtomic(uint32_t) * nB, bool useOrigTrackParam)
{
  //* prepare sector tracks for merging with next/previous/same sector
  //* each track transported to the border line
 
  float fieldBz = Param().bzCLight;
 
  float dAlpha = Param().par.dAlpha / 2;
  float x0 = 0;
 
  if (iBorder == 0) { // transport to the left edge of the sector and rotate horizontally
    dAlpha = dAlpha - CAMath::Pi() / 2;
  } else if (iBorder == 1) { // transport to the right edge of the sector and rotate horizontally
    dAlpha = -dAlpha - CAMath::Pi() / 2;
  } else if (iBorder == 2) { // transport to the middle of the sector and rotate vertically to the border on the left
    x0 = GPUTPCGeometry::Row2X(63);
  } else if (iBorder == 3) { // transport to the middle of the sector and rotate vertically to the border on the right
    dAlpha = -dAlpha;
    x0 = GPUTPCGeometry::Row2X(63);
  } else if (iBorder == 4) { // transport to the middle of the sßector, w/o rotation
    dAlpha = 0;
    x0 = GPUTPCGeometry::Row2X(63);
  }
 
  const float maxSin = CAMath::Sin(60.f / 180.f * CAMath::Pi());
  float cosAlpha = CAMath::Cos(dAlpha);
  float sinAlpha = CAMath::Sin(dAlpha);
 
  GPUTPCGMSectorTrack trackTmp;
  for (int32_t itr = iBlock * nThreads + iThread; itr < SectorTrackInfoLocalTotal(); itr += nThreads * nBlocks) {
    const GPUTPCGMSectorTrack* track = &mSectorTrackInfos[itr];
    int32_t iSector = track->Sector();
 
    if (track->PrevSegmentNeighbour() >= 0 && track->Sector() == mSectorTrackInfos[track->PrevSegmentNeighbour()].Sector()) {
      continue;
    }
    if (useOrigTrackParam) { // TODO: Check how far this makes sense with sector track refit
      if (CAMath::Abs(track->QPt()) * Param().qptB5Scaler < Param().rec.tpc.mergerLooperQPtB5Limit) {
        continue;
      }
      const GPUTPCGMSectorTrack* trackMin = track;
      while (track->NextSegmentNeighbour() >= 0 && track->Sector() == mSectorTrackInfos[track->NextSegmentNeighbour()].Sector()) {
        track = &mSectorTrackInfos[track->NextSegmentNeighbour()];
        if (track->OrigTrack()->Param().X() < trackMin->OrigTrack()->Param().X()) {
          trackMin = track;
        }
      }
      trackTmp = *trackMin;
      track = &trackTmp;
      if (Param().rec.tpc.mergerCovSource == 2 && trackTmp.X2() != 0.f) {
        trackTmp.UseParam2();
      } else {
        trackTmp.Set(this, trackMin->OrigTrack(), trackMin->Alpha(), trackMin->Sector());
      }
    } else {
      if (CAMath::Abs(track->QPt()) * Param().qptB5Scaler < Param().rec.tpc.mergerLooperSecondHorizontalQPtB5Limit) {
        if (iBorder == 0 && track->NextNeighbour() >= 0) {
          continue;
        }
        if (iBorder == 1 && track->PrevNeighbour() >= 0) {
          continue;
        }
      }
    }
    GPUTPCGMBorderTrack b;
 
    if (track->TransportToXAlpha(this, x0, sinAlpha, cosAlpha, fieldBz, b, maxSin)) {
      b.SetTrackID(itr);
      b.SetNClusters(track->NClusters());
      for (int32_t i = 0; i < 4; i++) {
        if (CAMath::Abs(b.Cov()[i]) >= 5.0f) {
          b.SetCov(i, 5.0f);
        }
      }
      if (CAMath::Abs(b.Cov()[4]) >= 0.5f) {
        b.SetCov(4, 0.5f);
      }
      uint32_t myTrack = CAMath::AtomicAdd(&nB[iSector], 1u);
      B[iSector][myTrack] = b;
    }
  }
}
 
template <>
GPUd() void GPUTPCGMMerger::MergeBorderTracks<0>(int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread, int32_t iSector1, GPUTPCGMBorderTrack* B1, int32_t N1, int32_t iSector2, GPUTPCGMBorderTrack* B2, int32_t N2, int32_t mergeMode)
{
  CADEBUG(GPUInfo("\nMERGING Sectors %d %d NTracks %d %d CROSS %d", iSector1, iSector2, N1, N2, mergeMode));
  GPUTPCGMBorderRange* range1 = mBorderRange[iSector1];
  GPUTPCGMBorderRange* range2 = mBorderRange[iSector2] + *GetConstantMem()->tpcTrackers[iSector2].NTracks();
  bool sameSector = (iSector1 == iSector2);
  for (int32_t itr = iBlock * nThreads + iThread; itr < N1; itr += nThreads * nBlocks) {
    GPUTPCGMBorderTrack& b = B1[itr];
    float d = CAMath::Max(0.5f, 3.5f * CAMath::Sqrt(b.Cov()[1]));
    if (CAMath::Abs(b.Par()[4]) * Param().qptB5Scaler >= 20) {
      d *= 2;
    } else if (d > 3) {
      d = 3;
    }
    CADEBUG(printf("  Input Sector 1 %d Track %d: ", iSector1, itr); for (int32_t i = 0; i < 5; i++) { printf("%8.3f ", b.Par()[i]); } printf(" - "); for (int32_t i = 0; i < 5; i++) { printf("%8.3f ", b.Cov()[i]); } printf(" - D %8.3f\n", d));
    GPUTPCGMBorderRange range;
    range.fId = itr;
    range.fMin = b.Par()[1] + b.ZOffsetLinear() - d;
    range.fMax = b.Par()[1] + b.ZOffsetLinear() + d;
    range1[itr] = range;
    if (sameSector) {
      range2[itr] = range;
    }
  }
  if (!sameSector) {
    for (int32_t itr = iBlock * nThreads + iThread; itr < N2; itr += nThreads * nBlocks) {
      GPUTPCGMBorderTrack& b = B2[itr];
      float d = CAMath::Max(0.5f, 3.5f * CAMath::Sqrt(b.Cov()[1]));
      if (CAMath::Abs(b.Par()[4]) * Param().qptB5Scaler >= 20) {
        d *= 2;
      } else if (d > 3) {
        d = 3;
      }
      CADEBUG(printf("  Input Sector 2 %d Track %d: ", iSector2, itr); for (int32_t i = 0; i < 5; i++) { printf("%8.3f ", b.Par()[i]); } printf(" - "); for (int32_t i = 0; i < 5; i++) { printf("%8.3f ", b.Cov()[i]); } printf(" - D %8.3f\n", d));
      GPUTPCGMBorderRange range;
      range.fId = itr;
      range.fMin = b.Par()[1] + b.ZOffsetLinear() - d;
      range.fMax = b.Par()[1] + b.ZOffsetLinear() + d;
      range2[itr] = range;
    }
  }
}
 
template <>
GPUd() void GPUTPCGMMerger::MergeBorderTracks<1>(int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread, int32_t iSector1, GPUTPCGMBorderTrack* B1, int32_t N1, int32_t iSector2, GPUTPCGMBorderTrack* B2, int32_t N2, int32_t mergeMode)
{
#if !defined(GPUCA_GPUCODE_COMPILEKERNELS)
  GPUTPCGMBorderRange* range1 = mBorderRange[iSector1];
  GPUTPCGMBorderRange* range2 = mBorderRange[iSector2] + *GetConstantMem()->tpcTrackers[iSector2].NTracks();
 
  if (iThread == 0) {
    if (iBlock == 0) {
      GPUCommonAlgorithm::sortDeviceDynamic(range1, range1 + N1, [](const GPUTPCGMBorderRange& a, const GPUTPCGMBorderRange& b) { return GPUCA_DETERMINISTIC_CODE((a.fMin != b.fMin) ? (a.fMin < b.fMin) : (a.fId < b.fId), a.fMin < b.fMin); });
    } else if (iBlock == 1) {
      GPUCommonAlgorithm::sortDeviceDynamic(range2, range2 + N2, [](const GPUTPCGMBorderRange& a, const GPUTPCGMBorderRange& b) { return GPUCA_DETERMINISTIC_CODE((a.fMax != b.fMax) ? (a.fMax < b.fMax) : (a.fId < b.fId), a.fMax < b.fMax); });
    }
  }
#else
  printf("This sorting variant is disabled for RTC");
#endif
}
 
template <>
GPUd() void GPUTPCGMMerger::MergeBorderTracks<3>(int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread, GPUTPCGMBorderRange* range, int32_t N, int32_t cmpMax)
{
#ifndef GPUCA_SPECIALIZE_THRUST_SORTS
  if (iThread == 0) {
    if (cmpMax) {
      GPUCommonAlgorithm::sortDeviceDynamic(range, range + N, [](const GPUTPCGMBorderRange& a, const GPUTPCGMBorderRange& b) { return GPUCA_DETERMINISTIC_CODE((a.fMax != b.fMax) ? (a.fMax < b.fMax) : (a.fId < b.fId), a.fMax < b.fMax); });
    } else {
      GPUCommonAlgorithm::sortDeviceDynamic(range, range + N, [](const GPUTPCGMBorderRange& a, const GPUTPCGMBorderRange& b) { return GPUCA_DETERMINISTIC_CODE((a.fMin != b.fMin) ? (a.fMin < b.fMin) : (a.fId < b.fId), a.fMin < b.fMin); });
    }
  }
#endif
}
 
template <>
GPUd() void GPUTPCGMMerger::MergeBorderTracks<2>(int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread, int32_t iSector1, GPUTPCGMBorderTrack* B1, int32_t N1, int32_t iSector2, GPUTPCGMBorderTrack* B2, int32_t N2, int32_t mergeMode)
{
  // int32_t statAll = 0, statMerged = 0;
  float factor2ys = Param().rec.tpc.trackMergerFactor2YS;
  float factor2zt = Param().rec.tpc.trackMergerFactor2ZT;
  float factor2k = Param().rec.tpc.trackMergerFactor2K;
  float factor2General = Param().rec.tpc.trackMergerFactor2General;
 
  factor2k = factor2General * factor2k;
  factor2ys = factor2General * factor2ys;
  factor2zt = factor2General * factor2zt;
 
  int32_t minNPartHits = Param().rec.tpc.trackMergerMinPartHits;
  int32_t minNTotalHits = Param().rec.tpc.trackMergerMinTotalHits;
 
  bool sameSector = (iSector1 == iSector2);
 
  GPUTPCGMBorderRange* range1 = mBorderRange[iSector1];
  GPUTPCGMBorderRange* range2 = mBorderRange[iSector2] + *GetConstantMem()->tpcTrackers[iSector2].NTracks();
 
  int32_t i2 = 0;
  for (int32_t i1 = iBlock * nThreads + iThread; i1 < N1; i1 += nThreads * nBlocks) {
    GPUTPCGMBorderRange r1 = range1[i1];
    while (i2 < N2 && range2[i2].fMax < r1.fMin) {
      i2++;
    }
 
    GPUTPCGMBorderTrack& b1 = B1[r1.fId];
    if (b1.NClusters() < minNPartHits) {
      continue;
    }
    int32_t iBest2 = -1;
    int32_t lBest2 = 0;
    // statAll++;
    for (int32_t k2 = i2; k2 < N2; k2++) {
      GPUTPCGMBorderRange r2 = range2[k2];
      if (r2.fMin > r1.fMax) {
        break;
      }
      if (sameSector && (r1.fId >= r2.fId)) {
        continue;
      }
      // do check
 
      GPUTPCGMBorderTrack& b2 = B2[r2.fId];
#if defined(GPUCA_MERGER_BY_MC_LABEL) && !defined(GPUCA_GPUCODE)
      int64_t label1 = GetTrackLabel(b1);
      int64_t label2 = GetTrackLabel(b2);
      if (label1 != label2 && label1 != -1) // DEBUG CODE, match by MC label
#endif
      {
        CADEBUG(if (GetConstantMem()->ioPtrs.mcLabelsTPC) {printf("Comparing track %3d to %3d: ", r1.fId, r2.fId); for (int32_t i = 0; i < 5; i++) { printf("%8.3f ", b1.Par()[i]); } printf(" - "); for (int32_t i = 0; i < 5; i++) { printf("%8.3f ", b1.Cov()[i]); } printf("\n%28s", ""); });
        CADEBUG(if (GetConstantMem()->ioPtrs.mcLabelsTPC) {for (int32_t i = 0; i < 5; i++) { printf("%8.3f ", b2.Par()[i]); } printf(" - "); for (int32_t i = 0; i < 5; i++) { printf("%8.3f ", b2.Cov()[i]); } printf("   -   %5s   -   ", GetTrackLabel(b1) == GetTrackLabel(b2) ? "CLONE" : "FAKE"); });
        if (b2.NClusters() < lBest2) {
          CADEBUG2(continue, printf("!NCl1\n"));
        }
        if (mergeMode > 0) {
          // Merging CE tracks
          int32_t maxRowDiff = mergeMode == 2 ? 1 : 3; // TODO: check cut
          if (CAMath::Abs(b1.Row() - b2.Row()) > maxRowDiff) {
            CADEBUG2(continue, printf("!ROW\n"));
          }
          if (CAMath::Abs(b1.Par()[2] - b2.Par()[2]) > 0.5f || CAMath::Abs(b1.Par()[3] - b2.Par()[3]) > 0.5f) {
            CADEBUG2(continue, printf("!CE SinPhi/Tgl\n")); // Crude cut to avoid totally wrong matches, TODO: check cut
          }
        }
 
        GPUCA_DEBUG_STREAMER_CHECK(float weight = b1.Par()[4] * b1.Par()[4]; if (o2::utils::DebugStreamer::checkStream(o2::utils::StreamFlags::streamMergeBorderTracksAll, b1.TrackID(), weight)) { MergedTrackStreamer(b1, b2, "merge_all_tracks", iSector1, iSector2, mergeMode, weight, o2::utils::DebugStreamer::getSamplingFrequency(o2::utils::StreamFlags::streamMergeBorderTracksAll)); });
 
        if (!b1.CheckChi2Y(b2, factor2ys)) {
          CADEBUG2(continue, printf("!Y\n"));
        }
        // if( !b1.CheckChi2Z(b2, factor2zt ) ) CADEBUG2(continue, printf("!NCl1\n"));
        if (!b1.CheckChi2QPt(b2, factor2k)) {
          CADEBUG2(continue, printf("!QPt\n"));
        }
        float fys = CAMath::Abs(b1.Par()[4]) * Param().qptB5Scaler < 20 ? factor2ys : (2.f * factor2ys);
        float fzt = CAMath::Abs(b1.Par()[4]) * Param().qptB5Scaler < 20 ? factor2zt : (2.f * factor2zt);
        if (!b1.CheckChi2YS(b2, fys)) {
          CADEBUG2(continue, printf("!YS\n"));
        }
        if (!b1.CheckChi2ZT(b2, fzt)) {
          CADEBUG2(continue, printf("!ZT\n"));
        }
        if (CAMath::Abs(b1.Par()[4]) * Param().qptB5Scaler < 20) {
          if (b2.NClusters() < minNPartHits) {
            CADEBUG2(continue, printf("!NCl2\n"));
          }
          if (b1.NClusters() + b2.NClusters() < minNTotalHits) {
            CADEBUG2(continue, printf("!NCl3\n"));
          }
        }
        CADEBUG(printf("OK: dZ %8.3f D1 %8.3f D2 %8.3f\n", CAMath::Abs(b1.Par()[1] - b2.Par()[1]), 3.5f * sqrt(b1.Cov()[1]), 3.5f * sqrt(b2.Cov()[1])));
      } // DEBUG CODE, match by MC label
      lBest2 = b2.NClusters();
      iBest2 = b2.TrackID();
    }
 
    if (iBest2 < 0) {
      continue;
    }
    GPUCA_DEBUG_STREAMER_CHECK(float weight = b1.Par()[4] * b1.Par()[4]; if (o2::utils::DebugStreamer::checkStream(o2::utils::StreamFlags::streamMergeBorderTracksBest, b1.TrackID(), weight)) { MergedTrackStreamer(b1, MergedTrackStreamerFindBorderTrack(B2, N2, iBest2), "merge_best_track", iSector1, iSector2, mergeMode, weight, o2::utils::DebugStreamer::getSamplingFrequency(o2::utils::StreamFlags::streamMergeBorderTracksBest)); });
 
    // statMerged++;
 
    CADEBUG(GPUInfo("Found match %d %d", b1.TrackID(), iBest2));
 
    mTrackLinks[b1.TrackID()] = iBest2;
    if (mergeMode > 0) {
      GPUCA_DETERMINISTIC_CODE(CAMath::AtomicMax(&mTrackLinks[iBest2], b1.TrackID()), mTrackLinks[iBest2] = b1.TrackID());
    }
  }
  // GPUInfo("STAT: sectors %d, %d: all %d merged %d", iSector1, iSector2, statAll, statMerged);
}
 
GPUdii() void GPUTPCGMMerger::MergeBorderTracksSetup(int32_t& n1, int32_t& n2, GPUTPCGMBorderTrack*& b1, GPUTPCGMBorderTrack*& b2, int32_t& jSector, int32_t iSector, int8_t withinSector, int8_t mergeMode) const
{
  if (withinSector == 1) { // Merge tracks within the same sector
    jSector = iSector;
    n1 = n2 = mMemory->tmpCounter[iSector];
    b1 = b2 = mBorder[iSector];
  } else if (withinSector == -1) { // Merge tracks accross the central electrode
    jSector = (iSector + NSECTORS / 2);
    const int32_t offset = mergeMode == 2 ? NSECTORS : 0;
    n1 = mMemory->tmpCounter[iSector + offset];
    n2 = mMemory->tmpCounter[jSector + offset];
    b1 = mBorder[iSector + offset];
    b2 = mBorder[jSector + offset];
  } else { // Merge tracks of adjacent sectors
    jSector = mNextSectorInd[iSector];
    n1 = mMemory->tmpCounter[iSector];
    n2 = mMemory->tmpCounter[NSECTORS + jSector];
    b1 = mBorder[iSector];
    b2 = mBorder[NSECTORS + jSector];
  }
}
 
template <int32_t I>
GPUd() void GPUTPCGMMerger::MergeBorderTracks(int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread, int32_t iSector, int8_t withinSector, int8_t mergeMode)
{
  int32_t n1, n2;
  GPUTPCGMBorderTrack *b1, *b2;
  int32_t jSector;
  MergeBorderTracksSetup(n1, n2, b1, b2, jSector, iSector, withinSector, mergeMode);
  MergeBorderTracks<I>(nBlocks, nThreads, iBlock, iThread, iSector, b1, n1, jSector, b2, n2, mergeMode);
}
 
#if !defined(GPUCA_GPUCODE) || defined(GPUCA_GPUCODE_DEVICE) // FIXME: DR: WORKAROUND to avoid CUDA bug creating host symbols for device code.
template GPUdni() void GPUTPCGMMerger::MergeBorderTracks<0>(int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread, int32_t iSector, int8_t withinSector, int8_t mergeMode);
template GPUdni() void GPUTPCGMMerger::MergeBorderTracks<1>(int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread, int32_t iSector, int8_t withinSector, int8_t mergeMode);
template GPUdni() void GPUTPCGMMerger::MergeBorderTracks<2>(int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread, int32_t iSector, int8_t withinSector, int8_t mergeMode);
#endif
 
GPUd() void GPUTPCGMMerger::MergeWithinSectorsPrepare(int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread)
{
  float x0 = GPUTPCGeometry::Row2X(63);
  const float maxSin = CAMath::Sin(60.f / 180.f * CAMath::Pi());
 
  for (int32_t itr = iBlock * nThreads + iThread; itr < SectorTrackInfoLocalTotal(); itr += nThreads * nBlocks) {
    GPUTPCGMSectorTrack& track = mSectorTrackInfos[itr];
    int32_t iSector = track.Sector();
    GPUTPCGMBorderTrack b;
    if (track.TransportToX(this, x0, Param().bzCLight, b, maxSin)) {
      b.SetTrackID(itr);
      CADEBUG(printf("WITHIN SECTOR %d Track %d - ", iSector, itr); for (int32_t i = 0; i < 5; i++) { printf("%8.3f ", b.Par()[i]); } printf(" - "); for (int32_t i = 0; i < 5; i++) { printf("%8.3f ", b.Cov()[i]); } printf("\n"));
      b.SetNClusters(track.NClusters());
      uint32_t myTrack = CAMath::AtomicAdd(&mMemory->tmpCounter[iSector], 1u);
      mBorder[iSector][myTrack] = b;
    }
  }
}
 
GPUd() void GPUTPCGMMerger::MergeSectorsPrepare(int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread, int32_t border0, int32_t border1, int8_t useOrigTrackParam)
{
  bool part2 = iBlock & 1;
  int32_t border = part2 ? border1 : border0;
  GPUAtomic(uint32_t)* n = mMemory->tmpCounter;
  GPUTPCGMBorderTrack** b = mBorder;
  if (part2) {
    n += NSECTORS;
    b += NSECTORS;
  }
  MergeSectorsPrepareStep2((nBlocks + !part2) >> 1, nThreads, iBlock >> 1, iThread, border, b, n, useOrigTrackParam);
}
 
GPUdi() void GPUTPCGMMerger::setBlockRange(int32_t elems, int32_t nBlocks, int32_t iBlock, int32_t& start, int32_t& end)
{
  start = (elems + nBlocks - 1) / nBlocks * iBlock;
  end = (elems + nBlocks - 1) / nBlocks * (iBlock + 1);
  end = CAMath::Min(elems, end);
}
 
GPUd() void GPUTPCGMMerger::hookEdge(int32_t u, int32_t v)
{
  if (v < 0) {
    return;
  }
  while (true) {
    u = mTrackCCRoots[u];
    v = mTrackCCRoots[v];
    if (u == v) {
      break;
    }
    int32_t h = CAMath::Max(u, v);
    int32_t l = CAMath::Min(u, v);
 
    int32_t old = CAMath::AtomicCAS(&mTrackCCRoots[h], h, l);
    if (old == h) {
      break;
    }
 
    u = mTrackCCRoots[h];
    v = l;
  }
}
 
GPUd() void GPUTPCGMMerger::ResolveFindConnectedComponentsSetup(int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread)
{
  int32_t start, end;
  setBlockRange(SectorTrackInfoLocalTotal(), nBlocks, iBlock, start, end);
  for (int32_t i = start + iThread; i < end; i += nThreads) {
    mTrackCCRoots[i] = i;
  }
}
 
GPUd() void GPUTPCGMMerger::ResolveFindConnectedComponentsHookLinks(int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread)
{
  // Compute connected components in parallel, step 1.
  // Source: Adaptive Work-Efficient Connected Components on the GPU, Sutton et al, 2016 (https://arxiv.org/pdf/1612.01178.pdf)
  int32_t start, end;
  setBlockRange(SectorTrackInfoLocalTotal(), nBlocks, iBlock, start, end);
  for (int32_t itr = start + iThread; itr < end; itr += nThreads) {
    hookEdge(itr, mTrackLinks[itr]);
  }
}
 
GPUd() void GPUTPCGMMerger::ResolveFindConnectedComponentsHookNeighbors(int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread)
{
  // Compute connected components in parallel, step 1 - Part 2.
  nBlocks = nBlocks / 4 * 4;
  if (iBlock >= nBlocks) {
    return;
  }
 
  int32_t start, end;
  setBlockRange(SectorTrackInfoLocalTotal(), nBlocks / 4, iBlock / 4, start, end);
 
  int32_t myNeighbor = iBlock % 4;
 
  for (int32_t itr = start + iThread; itr < end; itr += nThreads) {
    int32_t v = mSectorTrackInfos[itr].AnyNeighbour(myNeighbor);
    hookEdge(itr, v);
  }
}
 
GPUd() void GPUTPCGMMerger::ResolveFindConnectedComponentsMultiJump(int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread)
{
  // Compute connected components in parallel, step 2.
  int32_t start, end;
  setBlockRange(SectorTrackInfoLocalTotal(), nBlocks, iBlock, start, end);
  for (int32_t itr = start + iThread; itr < end; itr += nThreads) {
    int32_t root = itr;
    int32_t next = mTrackCCRoots[root];
    if (root == next) {
      continue;
    }
    do {
      root = next;
      next = mTrackCCRoots[next];
    } while (root != next);
    mTrackCCRoots[itr] = root;
  }
}
 
GPUd() void GPUTPCGMMerger::ResolveMergeSectors(GPUResolveSharedMemory& smem, int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread, int8_t useOrigTrackParam, int8_t mergeAll)
{
  if (!mergeAll) {
    /*int32_t neighborType = useOrigTrackParam ? 1 : 0;
    int32_t old1 = newTrack2.PrevNeighbour(0);
    int32_t old2 = newTrack1.NextNeighbour(0);
    if (old1 < 0 && old2 < 0) neighborType = 0;
    if (old1 == itr) continue;
    if (neighborType) old1 = newTrack2.PrevNeighbour(1);
    if ( old1 >= 0 )
    {
        GPUTPCGMSectorTrack &oldTrack1 = mSectorTrackInfos[old1];
        if ( oldTrack1.NClusters() < newTrack1.NClusters() ) {
            newTrack2.SetPrevNeighbour( -1, neighborType );
            oldTrack1.SetNextNeighbour( -1, neighborType );
        } else continue;
    }
 
    if (old2 == itr2) continue;
    if (neighborType) old2 = newTrack1.NextNeighbour(1);
    if ( old2 >= 0 )
    {
        GPUTPCGMSectorTrack &oldTrack2 = mSectorTrackInfos[old2];
        if ( oldTrack2.NClusters() < newTrack2.NClusters() )
        {
        oldTrack2.SetPrevNeighbour( -1, neighborType );
        } else continue;
    }
    newTrack1.SetNextNeighbour( itr2, neighborType );
    newTrack2.SetPrevNeighbour( itr, neighborType );*/
  }
 
  int32_t start, end;
  setBlockRange(SectorTrackInfoLocalTotal(), nBlocks, iBlock, start, end);
 
  for (int32_t baseIdx = 0; baseIdx < SectorTrackInfoLocalTotal(); baseIdx += nThreads) {
    int32_t itr = baseIdx + iThread;
    bool inRange = itr < SectorTrackInfoLocalTotal();
 
    int32_t itr2 = -1;
    if (inRange) {
      itr2 = mTrackLinks[itr];
    }
 
    bool resolveSector = (itr2 > -1);
    if (resolveSector) {
      int32_t root = mTrackCCRoots[itr];
      resolveSector &= (start <= root) && (root < end);
    }
 
    int16_t smemIdx = work_group_scan_inclusive_add(int16_t(resolveSector));
 
    if (resolveSector) {
      smem.iTrack1[smemIdx - 1] = itr;
      smem.iTrack2[smemIdx - 1] = itr2;
    }
    GPUbarrier();
 
    if (iThread < nThreads - 1) {
      continue;
    }
 
    const int32_t nSectors = smemIdx;
 
    for (int32_t i = 0; i < nSectors; i++) {
      itr = smem.iTrack1[i];
      itr2 = smem.iTrack2[i];
 
      GPUTPCGMSectorTrack* track1 = &mSectorTrackInfos[itr];
      GPUTPCGMSectorTrack* track2 = &mSectorTrackInfos[itr2];
      GPUTPCGMSectorTrack* track1Base = track1;
      GPUTPCGMSectorTrack* track2Base = track2;
 
      bool sameSegment = CAMath::Abs(track1->NClusters() > track2->NClusters() ? track1->QPt() : track2->QPt()) * Param().qptB5Scaler < 2 || track1->QPt() * track2->QPt() > 0;
      // GPUInfo("\nMerge %d with %d - same segment %d", itr, itr2, (int32_t) sameSegment);
      // PrintMergeGraph(track1, std::cout);
      // PrintMergeGraph(track2, std::cout);
 
      while (track2->PrevSegmentNeighbour() >= 0) {
        track2 = &mSectorTrackInfos[track2->PrevSegmentNeighbour()];
      }
      if (sameSegment) {
        if (track1 == track2) {
          continue;
        }
        while (track1->PrevSegmentNeighbour() >= 0) {
          track1 = &mSectorTrackInfos[track1->PrevSegmentNeighbour()];
          if (track1 == track2) {
            goto NextTrack;
          }
        }
        GPUCommonAlgorithm::swap(track1, track1Base);
        for (int32_t k = 0; k < 2; k++) {
          GPUTPCGMSectorTrack* tmp = track1Base;
          while (tmp->Neighbour(k) >= 0) {
            tmp = &mSectorTrackInfos[tmp->Neighbour(k)];
            if (tmp == track2) {
              goto NextTrack;
            }
          }
        }
 
        while (track1->NextSegmentNeighbour() >= 0) {
          track1 = &mSectorTrackInfos[track1->NextSegmentNeighbour()];
          if (track1 == track2) {
            goto NextTrack;
          }
        }
      } else {
        while (track1->PrevSegmentNeighbour() >= 0) {
          track1 = &mSectorTrackInfos[track1->PrevSegmentNeighbour()];
        }
 
        if (track1 == track2) {
          continue;
        }
        for (int32_t k = 0; k < 2; k++) {
          GPUTPCGMSectorTrack* tmp = track1;
          while (tmp->Neighbour(k) >= 0) {
            tmp = &mSectorTrackInfos[tmp->Neighbour(k)];
            if (tmp == track2) {
              goto NextTrack;
            }
          }
        }
 
        float z1min, z1max, z2min, z2max;
        z1min = track1->MinClusterZT();
        z1max = track1->MaxClusterZT();
        z2min = track2->MinClusterZT();
        z2max = track2->MaxClusterZT();
        if (track1 != track1Base) {
          z1min = CAMath::Min(z1min, track1Base->MinClusterZT());
          z1max = CAMath::Max(z1max, track1Base->MaxClusterZT());
        }
        if (track2 != track2Base) {
          z2min = CAMath::Min(z2min, track2Base->MinClusterZT());
          z2max = CAMath::Max(z2max, track2Base->MaxClusterZT());
        }
        bool goUp = z2max - z1min > z1max - z2min;
 
        if (track1->Neighbour(goUp) < 0 && track2->Neighbour(!goUp) < 0) {
          track1->SetNeighbor(track2 - mSectorTrackInfos, goUp);
          track2->SetNeighbor(track1 - mSectorTrackInfos, !goUp);
          // GPUInfo("Result (simple neighbor)");
          // PrintMergeGraph(track1, std::cout);
          continue;
        } else if (track1->Neighbour(goUp) < 0) {
          track2 = &mSectorTrackInfos[track2->Neighbour(!goUp)];
          GPUCommonAlgorithm::swap(track1, track2);
        } else if (track2->Neighbour(!goUp) < 0) {
          track1 = &mSectorTrackInfos[track1->Neighbour(goUp)];
        } else { // Both would work, but we use the simpler one
          track1 = &mSectorTrackInfos[track1->Neighbour(goUp)];
        }
        track1Base = track1;
      }
 
      track2Base = track2;
      if (!sameSegment) {
        while (track1->NextSegmentNeighbour() >= 0) {
          track1 = &mSectorTrackInfos[track1->NextSegmentNeighbour()];
        }
      }
      track1->SetNextSegmentNeighbour(track2 - mSectorTrackInfos);
      track2->SetPrevSegmentNeighbour(track1 - mSectorTrackInfos);
      // k = 0: Merge right side
      // k = 1: Merge left side
      for (int32_t k = 0; k < 2; k++) {
        track1 = track1Base;
        track2 = track2Base;
        while (track2->Neighbour(k) >= 0) {
          if (track1->Neighbour(k) >= 0) {
            GPUTPCGMSectorTrack* track1new = &mSectorTrackInfos[track1->Neighbour(k)];
            GPUTPCGMSectorTrack* track2new = &mSectorTrackInfos[track2->Neighbour(k)];
            track2->SetNeighbor(-1, k);
            track2new->SetNeighbor(-1, k ^ 1);
            track1 = track1new;
            while (track1->NextSegmentNeighbour() >= 0) {
              track1 = &mSectorTrackInfos[track1->NextSegmentNeighbour()];
            }
            track1->SetNextSegmentNeighbour(track2new - mSectorTrackInfos);
            track2new->SetPrevSegmentNeighbour(track1 - mSectorTrackInfos);
            track1 = track1new;
            track2 = track2new;
          } else {
            GPUTPCGMSectorTrack* track2new = &mSectorTrackInfos[track2->Neighbour(k)];
            track1->SetNeighbor(track2->Neighbour(k), k);
            track2->SetNeighbor(-1, k);
            track2new->SetNeighbor(track1 - mSectorTrackInfos, k ^ 1);
          }
        }
      }
      // GPUInfo("Result");
      // PrintMergeGraph(track1, std::cout);
    NextTrack:;
    }
  }
}
 
GPUd() void GPUTPCGMMerger::MergeCEFill(const GPUTPCGMSectorTrack* track, const GPUTPCGMMergedTrackHit& cls, const GPUTPCGMMergedTrackHitXYZ* clsXYZ, int32_t itr)
{
  if (Param().rec.tpc.mergerCERowLimit > 0 && CAMath::Abs(track->QPt()) * Param().qptB5Scaler < 0.3f && (cls.row < Param().rec.tpc.mergerCERowLimit || cls.row >= GPUCA_ROW_COUNT - Param().rec.tpc.mergerCERowLimit)) {
    return;
  }
 
  float z = 0;
  if (Param().par.earlyTpcTransform) {
    z = clsXYZ->z;
  } else {
    float x, y;
    auto& cln = mConstantMem->ioPtrs.clustersNative->clustersLinear[cls.num];
    GPUTPCConvertImpl::convert(*mConstantMem, cls.sector, cls.row, cln.getPad(), cln.getTime(), x, y, z);
  }
 
  if (!Param().par.continuousTracking && CAMath::Abs(z) > 10) {
    return;
  }
  int32_t sector = track->Sector();
  for (int32_t attempt = 0; attempt < 2; attempt++) {
    GPUTPCGMBorderTrack b;
    const float x0 = GPUTPCGeometry::Row2X(attempt == 0 ? 63 : cls.row);
    if (track->TransportToX(this, x0, Param().bzCLight, b, GPUCA_MAX_SIN_PHI_LOW)) {
      b.SetTrackID(itr);
      b.SetNClusters(mOutputTracks[itr].NClusters());
      if (CAMath::Abs(b.Cov()[4]) >= 0.5f) {
        b.SetCov(4, 0.5f); // TODO: Is this needed and better than the cut in BorderTrack?
      }
      if (track->CSide()) {
        b.SetPar(1, b.Par()[1] - 2 * (z - b.ZOffsetLinear()));
        b.SetZOffsetLinear(-b.ZOffsetLinear());
      }
      b.SetRow(cls.row);
      uint32_t id = sector + attempt * NSECTORS;
      uint32_t myTrack = CAMath::AtomicAdd(&mMemory->tmpCounter[id], 1u);
      mBorder[id][myTrack] = b;
      break;
    }
  }
}
 
GPUd() void GPUTPCGMMerger::MergeCE(int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread)
{
  const ClusterNative* cls = Param().par.earlyTpcTransform ? nullptr : mConstantMem->ioPtrs.clustersNative->clustersLinear;
  for (uint32_t i = iBlock * nThreads + iThread; i < mMemory->nOutputTracks; i += nThreads * nBlocks) {
    if (mOutputTracks[i].CSide() == 0 && mTrackLinks[i] >= 0) {
      if (mTrackLinks[mTrackLinks[i]] != (int32_t)i) {
        continue;
      }
      GPUTPCGMMergedTrack* trk[2] = {&mOutputTracks[i], &mOutputTracks[mTrackLinks[i]]};
 
      if (!trk[1]->OK() || trk[1]->CCE()) {
        continue;
      }
      bool celooper = (trk[0]->GetParam().GetQPt() * Param().qptB5Scaler > 1 && trk[0]->GetParam().GetQPt() * trk[1]->GetParam().GetQPt() < 0);
      bool looper = trk[0]->Looper() || trk[1]->Looper() || celooper;
      if (!looper && trk[0]->GetParam().GetPar(3) * trk[1]->GetParam().GetPar(3) < 0) {
        continue;
      }
 
      uint32_t newRef = CAMath::AtomicAdd(&mMemory->nOutputTrackClusters, trk[0]->NClusters() + trk[1]->NClusters());
      if (newRef + trk[0]->NClusters() + trk[1]->NClusters() >= mNMaxOutputTrackClusters) {
        raiseError(GPUErrors::ERROR_MERGER_CE_HIT_OVERFLOW, newRef + trk[0]->NClusters() + trk[1]->NClusters(), mNMaxOutputTrackClusters);
        for (uint32_t k = newRef; k < mNMaxOutputTrackClusters; k++) {
          mClusters[k].num = 0;
          mClusters[k].state = 0;
        }
        CAMath::AtomicExch(&mMemory->nOutputTrackClusters, mNMaxOutputTrackClusters);
        return;
      }
 
      bool needswap = false;
      if (looper) {
        float z0max, z1max;
        if (Param().par.earlyTpcTransform) {
          z0max = CAMath::Max(CAMath::Abs(mClustersXYZ[trk[0]->FirstClusterRef()].z), CAMath::Abs(mClustersXYZ[trk[0]->FirstClusterRef() + trk[0]->NClusters() - 1].z));
          z1max = CAMath::Max(CAMath::Abs(mClustersXYZ[trk[1]->FirstClusterRef()].z), CAMath::Abs(mClustersXYZ[trk[1]->FirstClusterRef() + trk[1]->NClusters() - 1].z));
        } else {
          z0max = -CAMath::Min(cls[mClusters[trk[0]->FirstClusterRef()].num].getTime(), cls[mClusters[trk[0]->FirstClusterRef() + trk[0]->NClusters() - 1].num].getTime());
          z1max = -CAMath::Min(cls[mClusters[trk[1]->FirstClusterRef()].num].getTime(), cls[mClusters[trk[1]->FirstClusterRef() + trk[1]->NClusters() - 1].num].getTime());
        }
        if (z1max < z0max) {
          needswap = true;
        }
      } else {
        if (mClusters[trk[0]->FirstClusterRef()].row > mClusters[trk[1]->FirstClusterRef()].row) {
          needswap = true;
        }
      }
      if (needswap) {
        GPUCommonAlgorithm::swap(trk[0], trk[1]);
      }
 
      bool reverse[2] = {false, false};
      if (looper) {
        if (Param().par.earlyTpcTransform) {
          reverse[0] = (mClustersXYZ[trk[0]->FirstClusterRef()].z > mClustersXYZ[trk[0]->FirstClusterRef() + trk[0]->NClusters() - 1].z) ^ (trk[0]->CSide() > 0);
          reverse[1] = (mClustersXYZ[trk[1]->FirstClusterRef()].z < mClustersXYZ[trk[1]->FirstClusterRef() + trk[1]->NClusters() - 1].z) ^ (trk[1]->CSide() > 0);
        } else {
          reverse[0] = cls[mClusters[trk[0]->FirstClusterRef()].num].getTime() < cls[mClusters[trk[0]->FirstClusterRef() + trk[0]->NClusters() - 1].num].getTime();
          reverse[1] = cls[mClusters[trk[1]->FirstClusterRef()].num].getTime() > cls[mClusters[trk[1]->FirstClusterRef() + trk[1]->NClusters() - 1].num].getTime();
        }
      }
 
      if (Param().par.continuousTracking) {
        if (Param().par.earlyTpcTransform) {
          const float z0 = trk[0]->CSide() ? CAMath::Max(mClustersXYZ[trk[0]->FirstClusterRef()].z, mClustersXYZ[trk[0]->FirstClusterRef() + trk[0]->NClusters() - 1].z) : CAMath::Min(mClustersXYZ[trk[0]->FirstClusterRef()].z, mClustersXYZ[trk[0]->FirstClusterRef() + trk[0]->NClusters() - 1].z);
          const float z1 = trk[1]->CSide() ? CAMath::Max(mClustersXYZ[trk[1]->FirstClusterRef()].z, mClustersXYZ[trk[1]->FirstClusterRef() + trk[1]->NClusters() - 1].z) : CAMath::Min(mClustersXYZ[trk[1]->FirstClusterRef()].z, mClustersXYZ[trk[1]->FirstClusterRef() + trk[1]->NClusters() - 1].z);
          const float offset = CAMath::Abs(z1) > CAMath::Abs(z0) ? -z0 : z1;
          trk[1]->Param().Z() += trk[1]->Param().TZOffset() - offset;
          trk[1]->Param().TZOffset() = offset;
        } else {
          GPUTPCGMMergedTrackHit* clsmax;
          const float tmax = CAMath::MaxWithRef(cls[mClusters[trk[0]->FirstClusterRef()].num].getTime(), cls[mClusters[trk[0]->FirstClusterRef() + trk[0]->NClusters() - 1].num].getTime(),
                                                cls[mClusters[trk[1]->FirstClusterRef()].num].getTime(), cls[mClusters[trk[1]->FirstClusterRef() + trk[1]->NClusters() - 1].num].getTime(),
                                                &mClusters[trk[0]->FirstClusterRef()], &mClusters[trk[0]->FirstClusterRef() + trk[0]->NClusters() - 1],
                                                &mClusters[trk[1]->FirstClusterRef()], &mClusters[trk[1]->FirstClusterRef() + trk[1]->NClusters() - 1], clsmax);
          const float offset = CAMath::Max(tmax - mConstantMem->calibObjects.fastTransformHelper->getCorrMap()->getMaxDriftTime(clsmax->sector, clsmax->row, cls[clsmax->num].getPad()), 0.f);
          trk[1]->Param().Z() += mConstantMem->calibObjects.fastTransformHelper->getCorrMap()->convDeltaTimeToDeltaZinTimeFrame(trk[1]->CSide() * NSECTORS / 2, trk[1]->Param().TZOffset() - offset);
          trk[1]->Param().TZOffset() = offset;
        }
      }
 
      int32_t pos = newRef;
      int32_t leg = -1;
      int32_t lastLeg = -1;
#pragma unroll
      for (int32_t k = 1; k >= 0; k--) {
        int32_t loopstart = reverse[k] ? (trk[k]->NClusters() - 1) : 0;
        int32_t loopend = reverse[k] ? -1 : (int32_t)trk[k]->NClusters();
        int32_t loopinc = reverse[k] ? -1 : 1;
        for (int32_t j = loopstart; j != loopend; j += loopinc) {
          if (Param().par.earlyTpcTransform) {
            mClustersXYZ[pos] = mClustersXYZ[trk[k]->FirstClusterRef() + j];
          }
          mClusters[pos] = mClusters[trk[k]->FirstClusterRef() + j];
          if (looper) {
            if (mClusters[trk[k]->FirstClusterRef() + j].leg != lastLeg) {
              leg++;
              lastLeg = mClusters[trk[k]->FirstClusterRef() + j].leg;
            }
            mClusters[pos].leg = leg;
          }
          pos++;
        }
        if (celooper) {
          lastLeg = -1;
        }
      }
      trk[1]->SetFirstClusterRef(newRef);
      trk[1]->SetNClusters(trk[0]->NClusters() + trk[1]->NClusters());
      if (trk[1]->NClusters() > GPUCA_MERGER_MAX_TRACK_CLUSTERS) {
        trk[1]->SetFirstClusterRef(trk[1]->FirstClusterRef() + trk[1]->NClusters() - GPUCA_MERGER_MAX_TRACK_CLUSTERS);
        trk[1]->SetNClusters(GPUCA_MERGER_MAX_TRACK_CLUSTERS);
      }
      trk[1]->SetCCE(true);
      if (looper) {
        trk[1]->SetLooper(true);
        trk[1]->SetLegs(leg + 1);
      }
      trk[0]->SetNClusters(0);
      trk[0]->SetOK(false);
    }
  }
 
  // for (int32_t i = 0;i < mMemory->nOutputTracks;i++) {if (mOutputTracks[i].CCE() == false) {mOutputTracks[i].SetNClusters(0);mOutputTracks[i].SetOK(false);}} //Remove all non-CE tracks
}
 
namespace o2::gpu::internal
{
namespace // anonymous
{
struct GPUTPCGMMerger_CompareClusterIdsLooper {
  struct clcomparestruct {
    uint8_t leg;
  };
 
  const uint8_t leg;
  const bool outwards;
  const GPUTPCGMMerger::trackCluster* const cmp1;
  const clcomparestruct* const cmp2;
  GPUd() GPUTPCGMMerger_CompareClusterIdsLooper(uint8_t l, bool o, const GPUTPCGMMerger::trackCluster* c1, const clcomparestruct* c2) : leg(l), outwards(o), cmp1(c1), cmp2(c2) {}
  GPUd() bool operator()(const int16_t aa, const int16_t bb)
  {
    const clcomparestruct& a = cmp2[aa];
    const clcomparestruct& b = cmp2[bb];
    const GPUTPCGMMerger::trackCluster& a1 = cmp1[aa];
    const GPUTPCGMMerger::trackCluster& b1 = cmp1[bb];
    if (a.leg != b.leg) {
      return ((leg > 0) ^ (a.leg > b.leg));
    }
    if (a1.row != b1.row) {
      return ((a1.row > b1.row) ^ ((a.leg - leg) & 1) ^ outwards);
    }
    return GPUCA_DETERMINISTIC_CODE((a1.id != b1.id) ? (a1.id > b1.id) : (aa > bb), a1.id > b1.id);
  }
};
 
struct GPUTPCGMMerger_CompareClusterIds {
  const GPUTPCGMMerger::trackCluster* const mCmp;
  GPUd() GPUTPCGMMerger_CompareClusterIds(const GPUTPCGMMerger::trackCluster* cmp) : mCmp(cmp) {}
  GPUd() bool operator()(const int16_t aa, const int16_t bb)
  {
    const GPUTPCGMMerger::trackCluster& a = mCmp[aa];
    const GPUTPCGMMerger::trackCluster& b = mCmp[bb];
    if (a.row != b.row) {
      return (a.row > b.row);
    }
    return GPUCA_DETERMINISTIC_CODE((a.id != b.id) ? (a.id > b.id) : (aa > bb), a.id > b.id);
  }
};
} // anonymous namespace
} // namespace o2::gpu::internal
 
GPUd() void GPUTPCGMMerger::CollectMergedTracks(int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread)
{
  GPUTPCGMSectorTrack* trackParts[kMaxParts];
 
  for (int32_t itr = iBlock * nThreads + iThread; itr < SectorTrackInfoLocalTotal(); itr += nThreads * nBlocks) {
 
    GPUTPCGMSectorTrack& track = mSectorTrackInfos[itr];
 
    if (track.PrevSegmentNeighbour() >= 0) {
      continue;
    }
    if (track.PrevNeighbour() >= 0) {
      continue;
    }
    int32_t nParts = 0;
    int32_t nHits = 0;
    int32_t leg = 0;
    GPUTPCGMSectorTrack *trbase = &track, *tr = &track;
    tr->SetPrevSegmentNeighbour(1000000000);
    while (true) {
      if (nParts >= kMaxParts) {
        break;
      }
      if (nHits + tr->NClusters() > kMaxClusters) {
        break;
      }
      nHits += tr->NClusters();
 
      tr->SetLeg(leg);
      trackParts[nParts++] = tr;
      for (int32_t i = 0; i < 2; i++) {
        if (tr->ExtrapolatedTrackId(i) != -1) {
          if (nParts >= kMaxParts) {
            break;
          }
          if (nHits + mSectorTrackInfos[tr->ExtrapolatedTrackId(i)].NClusters() > kMaxClusters) {
            break;
          }
          trackParts[nParts] = &mSectorTrackInfos[tr->ExtrapolatedTrackId(i)];
          trackParts[nParts++]->SetLeg(leg);
          nHits += mSectorTrackInfos[tr->ExtrapolatedTrackId(i)].NClusters();
        }
      }
      int32_t jtr = tr->NextSegmentNeighbour();
      if (jtr >= 0) {
        tr = &(mSectorTrackInfos[jtr]);
        tr->SetPrevSegmentNeighbour(1000000002);
        continue;
      }
      jtr = trbase->NextNeighbour();
      if (jtr >= 0) {
        trbase = &(mSectorTrackInfos[jtr]);
        tr = trbase;
        if (tr->PrevSegmentNeighbour() >= 0) {
          break;
        }
        tr->SetPrevSegmentNeighbour(1000000001);
        leg++;
        continue;
      }
      break;
    }
 
    // unpack and sort clusters
    if (nParts > 1 && leg == 0) {
      GPUCommonAlgorithm::sort(trackParts, trackParts + nParts, [](const GPUTPCGMSectorTrack* a, const GPUTPCGMSectorTrack* b) {
        GPUCA_DETERMINISTIC_CODE( // clang-format off
          if (a->X() != b->X()) {
            return (a->X() > b->X());
          }
          if (a->Y() != b->Y()) {
            return (a->Y() > b->Y());
          }
          if (a->Z() != b->Z()) {
            return (a->Z() > b->Z());
          }
          return a->QPt() > b->QPt();
        , // !GPUCA_DETERMINISTIC_CODE
          return (a->X() > b->X());
        ) // clang-format on
      });
    }
 
    if (Param().rec.tpc.dropLoopers && leg > 0) {
      nParts = 1;
      leg = 0;
    }
 
    trackCluster trackClusters[kMaxClusters];
    nHits = 0;
    for (int32_t ipart = 0; ipart < nParts; ipart++) {
      const GPUTPCGMSectorTrack* t = trackParts[ipart];
      CADEBUG(printf("Collect Track %d Part %d QPt %f DzDs %f\n", mMemory->nOutputTracks, ipart, t->QPt(), t->DzDs()));
      int32_t nTrackHits = t->NClusters();
      trackCluster* c2 = trackClusters + nHits + nTrackHits - 1;
      for (int32_t i = 0; i < nTrackHits; i++, c2--) {
        const GPUTPCTracker& trk = GetConstantMem()->tpcTrackers[t->Sector()];
        const GPUTPCHitId& ic = trk.TrackHits()[t->OrigTrack()->FirstHitID() + i];
        uint32_t id = trk.Data().ClusterDataIndex(trk.Data().Row(ic.RowIndex()), ic.HitIndex()) + GetConstantMem()->ioPtrs.clustersNative->clusterOffset[t->Sector()][0];
        *c2 = trackCluster{id, (uint8_t)ic.RowIndex(), t->Sector(), t->Leg()};
      }
      nHits += nTrackHits;
    }
    if (nHits < GPUCA_TRACKLET_SELECTOR_MIN_HITS_B5(track.QPt() * Param().qptB5Scaler)) {
      continue;
    }
 
    int32_t ordered = leg == 0;
    if (ordered) {
      for (int32_t i = 1; i < nHits; i++) {
        if (trackClusters[i].row > trackClusters[i - 1].row || trackClusters[i].id == trackClusters[i - 1].id) {
          ordered = 0;
          break;
        }
      }
    }
    int32_t firstTrackIndex = 0;
    int32_t lastTrackIndex = nParts - 1;
    if (ordered == 0) {
      int32_t nTmpHits = 0;
      trackCluster trackClustersUnsorted[kMaxClusters];
      int16_t clusterIndices[kMaxClusters];
      for (int32_t i = 0; i < nHits; i++) {
        trackClustersUnsorted[i] = trackClusters[i];
        clusterIndices[i] = i;
      }
 
      if (leg > 0) {
        // Find QPt and DzDs for the segment closest to the vertex, if low/mid Pt
        float baseZT = 1e9;
        uint8_t baseLeg = 0;
        for (int32_t i = 0; i < nParts; i++) {
          if (trackParts[i]->Leg() == 0 || trackParts[i]->Leg() == leg) {
            float zt;
            if (Param().par.earlyTpcTransform) {
              zt = CAMath::Min(CAMath::Abs(trackParts[i]->ClusterZT0()), CAMath::Abs(trackParts[i]->ClusterZTN()));
            } else {
              zt = -trackParts[i]->MinClusterZT(); // Negative time ~ smallest z, to behave the same way // TODO: Check all these min / max ZT
            }
            if (zt < baseZT) {
              baseZT = zt;
              baseLeg = trackParts[i]->Leg();
            }
          }
        }
        int32_t iLongest = 1e9;
        int32_t length = 0;
        for (int32_t i = (baseLeg ? (nParts - 1) : 0); baseLeg ? (i >= 0) : (i < nParts); baseLeg ? i-- : i++) {
          if (trackParts[i]->Leg() != baseLeg) {
            break;
          }
          if (trackParts[i]->OrigTrack()->NHits() > length) {
            iLongest = i;
            length = trackParts[i]->OrigTrack()->NHits();
          }
        }
        bool outwards;
        if (Param().par.earlyTpcTransform) {
          outwards = (trackParts[iLongest]->ClusterZT0() > trackParts[iLongest]->ClusterZTN()) ^ trackParts[iLongest]->CSide();
        } else {
          outwards = trackParts[iLongest]->ClusterZT0() < trackParts[iLongest]->ClusterZTN();
        }
        GPUTPCGMMerger_CompareClusterIdsLooper::clcomparestruct clusterSort[kMaxClusters];
        for (int32_t iPart = 0; iPart < nParts; iPart++) {
          const GPUTPCGMSectorTrack* t = trackParts[iPart];
          int32_t nTrackHits = t->NClusters();
          for (int32_t j = 0; j < nTrackHits; j++) {
            int32_t i = nTmpHits + j;
            clusterSort[i].leg = t->Leg();
          }
          nTmpHits += nTrackHits;
        }
 
        GPUCommonAlgorithm::sort(clusterIndices, clusterIndices + nHits, GPUTPCGMMerger_CompareClusterIdsLooper(baseLeg, outwards, trackClusters, clusterSort));
      } else {
        GPUCommonAlgorithm::sort(clusterIndices, clusterIndices + nHits, GPUTPCGMMerger_CompareClusterIds(trackClusters));
      }
      nTmpHits = 0;
      firstTrackIndex = lastTrackIndex = -1;
      for (int32_t i = 0; i < nParts; i++) {
        nTmpHits += trackParts[i]->NClusters();
        if (nTmpHits > clusterIndices[0] && firstTrackIndex == -1) {
          firstTrackIndex = i;
        }
        if (nTmpHits > clusterIndices[nHits - 1] && lastTrackIndex == -1) {
          lastTrackIndex = i;
        }
      }
 
      int32_t nFilteredHits = 0;
      int32_t indPrev = -1;
      for (int32_t i = 0; i < nHits; i++) {
        int32_t ind = clusterIndices[i];
        if (indPrev >= 0 && trackClustersUnsorted[ind].id == trackClustersUnsorted[indPrev].id) {
          continue;
        }
        indPrev = ind;
        trackClusters[nFilteredHits] = trackClustersUnsorted[ind];
        nFilteredHits++;
      }
      nHits = nFilteredHits;
    }
 
    const uint32_t iOutTrackFirstCluster = CAMath::AtomicAdd(&mMemory->nOutputTrackClusters, (uint32_t)nHits);
    if (iOutTrackFirstCluster >= mNMaxOutputTrackClusters) {
      raiseError(GPUErrors::ERROR_MERGER_HIT_OVERFLOW, iOutTrackFirstCluster, mNMaxOutputTrackClusters);
      CAMath::AtomicExch(&mMemory->nOutputTrackClusters, mNMaxOutputTrackClusters);
      continue;
    }
 
    GPUTPCGMMergedTrackHit* const cl = mClusters + iOutTrackFirstCluster;
 
    for (int32_t i = 0; i < nHits; i++) {
      uint8_t state;
      if (Param().par.earlyTpcTransform) {
        const GPUTPCClusterData& c = GetConstantMem()->tpcTrackers[trackClusters[i].sector].ClusterData()[trackClusters[i].id - GetConstantMem()->tpcTrackers[trackClusters[i].sector].Data().ClusterIdOffset()];
        GPUTPCGMMergedTrackHitXYZ* const clXYZ = mClustersXYZ + iOutTrackFirstCluster;
        clXYZ[i].x = c.x;
        clXYZ[i].y = c.y;
        clXYZ[i].z = c.z;
        clXYZ[i].amp = c.amp;
#ifdef GPUCA_TPC_RAW_PROPAGATE_PAD_ROW_TIME
        clXYZ[i].pad = c.mPad;
        clXYZ[i].time = c.mTime;
#endif
        state = c.flags;
      } else {
        const ClusterNative& c = GetConstantMem()->ioPtrs.clustersNative->clustersLinear[trackClusters[i].id];
        state = c.getFlags();
      }
      cl[i].state = state & GPUTPCGMMergedTrackHit::clustererAndSharedFlags; // Only allow edge, deconvoluted, and shared flags
      cl[i].row = trackClusters[i].row;
      cl[i].num = trackClusters[i].id;
      cl[i].sector = trackClusters[i].sector;
      cl[i].leg = trackClusters[i].leg;
    }
 
    uint32_t iOutputTrack = CAMath::AtomicAdd(&mMemory->nOutputTracks, 1u);
    if (iOutputTrack >= mNMaxTracks) {
      raiseError(GPUErrors::ERROR_MERGER_TRACK_OVERFLOW, iOutputTrack, mNMaxTracks);
      CAMath::AtomicExch(&mMemory->nOutputTracks, mNMaxTracks);
      continue;
    }
 
    GPUTPCGMMergedTrack& mergedTrack = mOutputTracks[iOutputTrack];
 
    mergedTrack.SetFlags(0);
    mergedTrack.SetOK(1);
    mergedTrack.SetLooper(leg > 0);
    mergedTrack.SetLegs(leg);
    mergedTrack.SetNClusters(nHits);
    mergedTrack.SetFirstClusterRef(iOutTrackFirstCluster);
    GPUTPCGMTrackParam& p1 = mergedTrack.Param();
    const GPUTPCGMSectorTrack& p2 = *trackParts[firstTrackIndex];
    mergedTrack.SetCSide(p2.CSide());
 
    GPUTPCGMBorderTrack b;
    const float toX = Param().par.earlyTpcTransform ? mClustersXYZ[iOutTrackFirstCluster].x : GPUTPCGeometry::Row2X(cl[0].row);
    if (p2.TransportToX(this, toX, Param().bzCLight, b, GPUCA_MAX_SIN_PHI, false)) {
      p1.X() = toX;
      p1.Y() = b.Par()[0];
      p1.Z() = b.Par()[1];
      p1.SinPhi() = b.Par()[2];
    } else {
      p1.X() = p2.X();
      p1.Y() = p2.Y();
      p1.Z() = p2.Z();
      p1.SinPhi() = p2.SinPhi();
    }
    p1.TZOffset() = p2.TZOffset();
    p1.DzDs() = p2.DzDs();
    p1.QPt() = p2.QPt();
    mergedTrack.SetAlpha(p2.Alpha());
    if (CAMath::Abs(Param().polynomialField.GetNominalBz()) < (gpu_common_constants::kZeroFieldCut * gpu_common_constants::kCLight)) {
      p1.QPt() = 100.f / Param().rec.bz0Pt10MeV;
    }
 
    // if (nParts > 1) printf("Merged %d: QPt %f %d parts %d hits\n", mMemory->nOutputTracks, p1.QPt(), nParts, nHits);
 
    /*if (GPUQA::QAAvailable() && mRec->GetQA() && mRec->GetQA()->SuppressTrack(mMemory->nOutputTracks))
    {
      mergedTrack.SetOK(0);
      mergedTrack.SetNClusters(0);
    }
    if (mergedTrack.NClusters() && mergedTrack.OK()) */
    if (Param().rec.tpc.mergeCE) {
      bool CEside;
      if (Param().par.earlyTpcTransform) {
        const GPUTPCGMMergedTrackHitXYZ* const clXYZ = mClustersXYZ + iOutTrackFirstCluster;
        CEside = (mergedTrack.CSide() != 0) ^ (clXYZ[0].z > clXYZ[nHits - 1].z);
      } else {
        auto& cls = mConstantMem->ioPtrs.clustersNative->clustersLinear;
        CEside = cls[cl[0].num].getTime() < cls[cl[nHits - 1].num].getTime();
      }
      MergeCEFill(trackParts[CEside ? lastTrackIndex : firstTrackIndex], cl[CEside ? (nHits - 1) : 0], Param().par.earlyTpcTransform ? &(mClustersXYZ + iOutTrackFirstCluster)[CEside ? (nHits - 1) : 0] : nullptr, iOutputTrack);
    }
  } // itr
}
 
GPUd() void GPUTPCGMMerger::SortTracksPrepare(int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread)
{
  for (uint32_t i = iBlock * nThreads + iThread; i < mMemory->nOutputTracks; i += nThreads * nBlocks) {
    mTrackOrderProcess[i] = i;
  }
}
 
GPUd() void GPUTPCGMMerger::PrepareClustersForFit0(int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread)
{
  for (uint32_t i = iBlock * nThreads + iThread; i < mMemory->nOutputTracks; i += nBlocks * nThreads) {
    mTrackSort[i] = i;
  }
}
 
GPUd() void GPUTPCGMMerger::SortTracks(int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread)
{
#ifndef GPUCA_SPECIALIZE_THRUST_SORTS
  if (iThread || iBlock) {
    return;
  }
  // TODO: Fix this: Have to duplicate sort comparison: Thrust cannot use the Lambda but OpenCL cannot use the object
  auto comp = [cmp = mOutputTracks](const int32_t aa, const int32_t bb) {
    const GPUTPCGMMergedTrack& GPUrestrict() a = cmp[aa];
    const GPUTPCGMMergedTrack& GPUrestrict() b = cmp[bb];
    if (a.CCE() != b.CCE()) {
      return a.CCE() > b.CCE();
    }
    if (a.Legs() != b.Legs()) {
      return a.Legs() > b.Legs();
    }
    GPUCA_DETERMINISTIC_CODE( // clang-format off
      if (a.NClusters() != b.NClusters()) {
        return a.NClusters() > b.NClusters();
      } if (CAMath::Abs(a.GetParam().GetQPt()) != CAMath::Abs(b.GetParam().GetQPt())) {
        return CAMath::Abs(a.GetParam().GetQPt()) > CAMath::Abs(b.GetParam().GetQPt());
      } if (a.GetParam().GetY() != b.GetParam().GetY()) {
        return a.GetParam().GetY() > b.GetParam().GetY();
      }
      return aa > bb;
    , // !GPUCA_DETERMINISTIC_CODE
      return a.NClusters() > b.NClusters();
    ) // clang-format on
  };
 
  GPUCommonAlgorithm::sortDeviceDynamic(mTrackOrderProcess, mTrackOrderProcess + mMemory->nOutputTracks, comp);
#endif
}
 
GPUd() void GPUTPCGMMerger::SortTracksQPt(int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread)
{
#ifndef GPUCA_SPECIALIZE_THRUST_SORTS
  if (iThread || iBlock) {
    return;
  }
  // TODO: Fix this: Have to duplicate sort comparison: Thrust cannot use the Lambda but OpenCL cannot use the object
  auto comp = [cmp = mOutputTracks](const int32_t aa, const int32_t bb) {
    const GPUTPCGMMergedTrack& GPUrestrict() a = cmp[aa];
    const GPUTPCGMMergedTrack& GPUrestrict() b = cmp[bb];
    GPUCA_DETERMINISTIC_CODE( // clang-format off
      if (CAMath::Abs(a.GetParam().GetQPt()) != CAMath::Abs(b.GetParam().GetQPt())) {
        return CAMath::Abs(a.GetParam().GetQPt()) > CAMath::Abs(b.GetParam().GetQPt());
      } if (a.GetParam().GetY() != b.GetParam().GetY()) {
        return a.GetParam().GetY() > b.GetParam().GetY();
      }
      return a.GetParam().GetZ() > b.GetParam().GetZ();
    , // !GPUCA_DETERMINISTIC_CODE
      return CAMath::Abs(a.GetParam().GetQPt()) > CAMath::Abs(b.GetParam().GetQPt());
    ) // clang-format on
  };
 
  GPUCommonAlgorithm::sortDeviceDynamic(mTrackSort, mTrackSort + mMemory->nOutputTracks, comp);
#endif
}
 
GPUd() void GPUTPCGMMerger::PrepareClustersForFit1(int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread)
{
  for (uint32_t i = iBlock * nThreads + iThread; i < mMemory->nOutputTracks; i += nBlocks * nThreads) {
    mTrackOrderAttach[mTrackSort[i]] = i;
    const GPUTPCGMMergedTrack& trk = mOutputTracks[i];
    if (trk.OK()) {
      for (uint32_t j = 0; j < trk.NClusters(); j++) {
        mClusterAttachment[mClusters[trk.FirstClusterRef() + j].num] = attachAttached | attachGood;
        CAMath::AtomicAdd(&mSharedCount[mClusters[trk.FirstClusterRef() + j].num], 1u);
      }
    }
  }
}
 
GPUd() void GPUTPCGMMerger::PrepareClustersForFit2(int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread)
{
  for (uint32_t i = iBlock * nThreads + iThread; i < mMemory->nOutputTrackClusters; i += nBlocks * nThreads) {
    if (mSharedCount[mClusters[i].num] > 1) {
      mClusters[i].state |= GPUTPCGMMergedTrackHit::flagShared;
    }
  }
  if (mClusterStateExt) {
    for (uint32_t i = iBlock * nThreads + iThread; i < mNMaxClusters; i += nBlocks * nThreads) {
      uint8_t state = GetConstantMem()->ioPtrs.clustersNative->clustersLinear[i].getFlags();
      if (mSharedCount[i] > 1) {
        state |= GPUTPCGMMergedTrackHit::flagShared;
      }
      mClusterStateExt[i] = state;
    }
  }
}
 
GPUd() void GPUTPCGMMerger::Finalize0(int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread)
{
  for (uint32_t i = iBlock * nThreads + iThread; i < mMemory->nOutputTracks; i += nThreads * nBlocks) {
    mTrackSort[mTrackOrderAttach[i]] = i;
  }
  for (uint32_t i = iBlock * nThreads + iThread; i < mMemory->nOutputTrackClusters; i += nThreads * nBlocks) {
    mClusterAttachment[mClusters[i].num] = 0; // Reset adjacent attachment for attached clusters, set correctly below
  }
}
 
GPUd() void GPUTPCGMMerger::Finalize1(int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread)
{
  for (uint32_t i = iBlock * nThreads + iThread; i < mMemory->nOutputTracks; i += nThreads * nBlocks) {
    const GPUTPCGMMergedTrack& trk = mOutputTracks[i];
    if (!trk.OK() || trk.NClusters() == 0) {
      continue;
    }
    uint8_t goodLeg = mClusters[trk.FirstClusterRef() + trk.NClusters() - 1].leg;
    for (uint32_t j = 0; j < trk.NClusters(); j++) {
      int32_t id = mClusters[trk.FirstClusterRef() + j].num;
      uint32_t weight = mTrackOrderAttach[i] | attachAttached;
      uint8_t clusterState = mClusters[trk.FirstClusterRef() + j].state;
      if (!(clusterState & GPUTPCGMMergedTrackHit::flagReject)) {
        weight |= attachGood;
      } else if (clusterState & GPUTPCGMMergedTrackHit::flagNotFit) {
        weight |= attachHighIncl;
      }
      if (mClusters[trk.FirstClusterRef() + j].leg == goodLeg) {
        weight |= attachGoodLeg;
      }
      CAMath::AtomicMax(&mClusterAttachment[id], weight);
    }
  }
}
 
GPUd() void GPUTPCGMMerger::Finalize2(int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread)
{
  for (uint32_t i = iBlock * nThreads + iThread; i < mNMaxClusters; i += nThreads * nBlocks) {
    if (mClusterAttachment[i] != 0) {
      mClusterAttachment[i] = (mClusterAttachment[i] & attachFlagMask) | mTrackSort[mClusterAttachment[i] & attachTrackMask];
    }
  }
}
 
GPUd() void GPUTPCGMMerger::MergeLoopersInit(int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread)
{
  const float lowPtThresh = Param().rec.tpc.rejectQPtB5 * 1.1f; // Might need to merge tracks above the threshold with parts below the threshold
  for (uint32_t i = get_global_id(0); i < mMemory->nOutputTracks; i += get_global_size(0)) {
    const auto& trk = mOutputTracks[i];
    const auto& p = trk.GetParam();
    const float qptabs = CAMath::Abs(p.GetQPt());
    if (trk.NClusters() && qptabs * Param().qptB5Scaler > 5.f && qptabs * Param().qptB5Scaler <= lowPtThresh) {
      const int32_t sector = mClusters[trk.FirstClusterRef() + trk.NClusters() - 1].sector;
      const float refz = p.GetZ() + (Param().par.earlyTpcTransform ? p.GetTZOffset() : GetConstantMem()->calibObjects.fastTransformHelper->getCorrMap()->convVertexTimeToZOffset(sector, p.GetTZOffset(), Param().continuousMaxTimeBin)) + (trk.CSide() ? -100 : 100);
      float sinA, cosA;
      CAMath::SinCos(trk.GetAlpha(), sinA, cosA);
      float gx = cosA * p.GetX() - sinA * p.GetY();
      float gy = cosA * p.GetY() + sinA * p.GetX();
      float bz = Param().polynomialField.GetFieldBz(gx, gy, p.GetZ());
      const float r1 = p.GetQPt() * bz;
      const float r = CAMath::Abs(r1) > 0.0001f ? (1.f / r1) : 10000;
      const float mx = p.GetX() + r * p.GetSinPhi();
      const float my = p.GetY() - r * CAMath::Sqrt(1 - p.GetSinPhi() * p.GetSinPhi());
      const float gmx = cosA * mx - sinA * my;
      const float gmy = cosA * my + sinA * mx;
      uint32_t myId = CAMath::AtomicAdd(&mMemory->nLooperMatchCandidates, 1u);
      if (myId >= mNMaxLooperMatches) {
        raiseError(GPUErrors::ERROR_LOOPER_MATCH_OVERFLOW, myId, mNMaxLooperMatches);
        CAMath::AtomicExch(&mMemory->nLooperMatchCandidates, mNMaxLooperMatches);
        return;
      }
      mLooperCandidates[myId] = MergeLooperParam{refz, gmx, gmy, i};
 
      /*printf("Track %u Sanity qpt %f snp %f bz %f\n", mMemory->nLooperMatchCandidates, p.GetQPt(), p.GetSinPhi(), bz);
      for (uint32_t k = 0;k < trk.NClusters();k++) {
        float xx, yy, zz;
        if (Param().par.earlyTpcTransform) {
          const float zOffset = (mClusters[trk.FirstClusterRef() + k].sector < 18) == (mClusters[trk.FirstClusterRef() + 0].sector < 18) ? p.GetTZOffset() : -p.GetTZOffset();
          xx = mClustersXYZ[trk.FirstClusterRef() + k].x;
          yy = mClustersXYZ[trk.FirstClusterRef() + k].y;
          zz = mClustersXYZ[trk.FirstClusterRef() + k].z - zOffset;
        } else {
          const ClusterNative& GPUrestrict() cl = GetConstantMem()->ioPtrs.clustersNative->clustersLinear[mClusters[trk.FirstClusterRef() + k].num];
          GetConstantMem()->calibObjects.fastTransformHelper->Transform(mClusters[trk.FirstClusterRef() + k].sector, mClusters[trk.FirstClusterRef() + k].row, cl.getPad(), cl.getTime(), xx, yy, zz, p.GetTZOffset());
        }
        float sa2, ca2;
        CAMath::SinCos(Param().Alpha(mClusters[trk.FirstClusterRef() + k].sector), sa2, ca2);
        float cx = ca2 * xx - sa2 * yy;
        float cy = ca2 * yy + sa2 * xx;
        float dist = CAMath::Sqrt((cx - gmx) * (cx - gmx) + (cy - gmy) * (cy - gmy));
        printf("Hit %3d/%3d sector %d xy %f %f R %f\n", k, trk.NClusters(), (int32_t)mClusters[trk.FirstClusterRef() + k].sector, cx, cy, dist);
      }*/
    }
  }
}
 
GPUd() void GPUTPCGMMerger::MergeLoopersSort(int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread)
{
#ifndef GPUCA_SPECIALIZE_THRUST_SORTS
  if (iThread || iBlock) {
    return;
  }
  auto comp = [](const MergeLooperParam& a, const MergeLooperParam& b) { return CAMath::Abs(a.refz) < CAMath::Abs(b.refz); };
  GPUCommonAlgorithm::sortDeviceDynamic(mLooperCandidates, mLooperCandidates + mMemory->nLooperMatchCandidates, comp);
#endif
}
 
GPUd() void GPUTPCGMMerger::MergeLoopersMain(int32_t nBlocks, int32_t nThreads, int32_t iBlock, int32_t iThread)
{
  const MergeLooperParam* params = mLooperCandidates;
 
#if GPUCA_MERGE_LOOPER_MC && !defined(GPUCA_GPUCODE)
  std::vector<int64_t> paramLabels(mMemory->nLooperMatchCandidates);
  for (uint32_t i = 0; i < mMemory->nLooperMatchCandidates; i++) {
    paramLabels[i] = GetTrackLabel(mOutputTracks[params[i].id]);
  }
  /*std::vector<bool> dropped(mMemory->nLooperMatchCandidates);
  std::vector<bool> droppedMC(mMemory->nLooperMatchCandidates);
  std::vector<int32_t> histMatch(101);
  std::vector<int32_t> histFail(101);*/
  if (!mRec->GetProcessingSettings().runQA) {
    throw std::runtime_error("Need QA enabled for the Merge Loopers MC QA");
  }
#endif
 
  for (uint32_t i = get_global_id(0); i < mMemory->nLooperMatchCandidates; i += get_global_size(0)) {
    for (uint32_t j = i + 1; j < mMemory->nLooperMatchCandidates; j++) {
      // int32_t bs = 0;
      if (CAMath::Abs(params[j].refz) > CAMath::Abs(params[i].refz) + 100.f) {
        break;
      }
      const float d2xy = CAMath::Sum2(params[i].x - params[j].x, params[i].y - params[j].y);
      if (d2xy > 15.f) {
        // bs |= 1;
        continue;
      }
      const auto& trk1 = mOutputTracks[params[i].id];
      const auto& trk2 = mOutputTracks[params[j].id];
      const auto& param1 = trk1.GetParam();
      const auto& param2 = trk2.GetParam();
      if (CAMath::Abs(param1.GetDzDs()) > 0.03f && CAMath::Abs(param2.GetDzDs()) > 0.03f && param1.GetDzDs() * param2.GetDzDs() * param1.GetQPt() * param2.GetQPt() < 0) {
        // bs |= 2;
        continue;
      }
 
      const float dznormalized = (CAMath::Abs(params[j].refz) - CAMath::Abs(params[i].refz)) / (CAMath::TwoPi() * 0.5f * (CAMath::Abs(param1.GetDzDs()) + CAMath::Abs(param2.GetDzDs())) * 1.f / (0.5f * (CAMath::Abs(param1.GetQPt()) + CAMath::Abs(param2.GetQPt())) * CAMath::Abs(Param().polynomialField.GetNominalBz())));
      const float phasecorr = CAMath::Modf((CAMath::ASin(param1.GetSinPhi()) + trk1.GetAlpha() - CAMath::ASin(param2.GetSinPhi()) - trk2.GetAlpha()) / CAMath::TwoPi() + 5.5f, 1.f) - 0.5f;
      const float phasecorrdirection = (params[j].refz * param1.GetQPt() * param1.GetDzDs()) > 0 ? 1 : -1;
      const float dzcorr = dznormalized + phasecorr * phasecorrdirection;
      const bool sameside = !(trk1.CSide() ^ trk2.CSide());
      const float dzcorrlimit[4] = {sameside ? 0.018f : 0.012f, sameside ? 0.12f : 0.025f, 0.14f, 0.15f};
      const int32_t dzcorrcount = sameside ? 4 : 2;
      bool dzcorrok = false;
      float dznorm = 0.f;
      for (int32_t k = 0; k < dzcorrcount; k++) {
        const float d = CAMath::Abs(dzcorr - 0.5f * k);
        if (d <= dzcorrlimit[k]) {
          dzcorrok = true;
          dznorm = d / dzcorrlimit[k];
          break;
        }
      }
      if (!dzcorrok) {
        // bs |= 4;
        continue;
      }
 
      const float dtgl = param1.GetDzDs() - (param1.GetQPt() * param2.GetQPt() > 0 ? param2.GetDzDs() : -param2.GetDzDs());
      const float dqpt = (CAMath::Abs(param1.GetQPt()) - CAMath::Abs(param2.GetQPt())) / CAMath::Min(param1.GetQPt(), param2.GetQPt());
      float d = CAMath::Sum2(dtgl * (1.f / 0.03f), dqpt * (1.f / 0.04f)) + d2xy * (1.f / 4.f) + dznorm * (1.f / 0.3f);
      bool EQ = d < 6.f;
#if GPUCA_MERGE_LOOPER_MC && !defined(GPUCA_GPUCODE)
      const int64_t label1 = paramLabels[i];
      const int64_t label2 = paramLabels[j];
      bool labelEQ = label1 != -1 && label1 == label2;
      if (1 || EQ || labelEQ) {
        // printf("Matching track %d/%d %u-%u (%ld/%ld): dist %f side %d %d, tgl %f %f, qpt %f %f, x %f %f, y %f %f\n", (int32_t)EQ, (int32_t)labelEQ, i, j, label1, label2, d, (int32_t)mOutputTracks[params[i].id].CSide(), (int32_t)mOutputTracks[params[j].id].CSide(), params[i].tgl, params[j].tgl, params[i].qpt, params[j].qpt, params[i].x, params[j].x, params[i].y, params[j].y);
        static auto& tup = GPUROOTDump<TNtuple>::get("mergeloopers", "labeleq:sides:d2xy:tgl1:tgl2:qpt1:qpt2:dz:dzcorr:dtgl:dqpt:dznorm:bs");
        tup.Fill((float)labelEQ, (trk1.CSide() ? 1 : 0) | (trk2.CSide() ? 2 : 0), d2xy, param1.GetDzDs(), param2.GetDzDs(), param1.GetQPt(), param2.GetQPt(), CAMath::Abs(params[j].refz) - CAMath::Abs(params[i].refz), dzcorr, dtgl, dqpt, dznorm, bs);
        static auto tup2 = GPUROOTDump<TNtuple>::getNew("mergeloopers2", "labeleq:refz1:refz2:tgl1:tgl2:qpt1:qpt2:snp1:snp2:a1:a2:dzn:phasecor:phasedir:dzcorr");
        tup2.Fill((float)labelEQ, params[i].refz, params[j].refz, param1.GetDzDs(), param2.GetDzDs(), param1.GetQPt(), param2.GetQPt(), param1.GetSinPhi(), param2.GetSinPhi(), trk1.GetAlpha(), trk2.GetAlpha(), dznormalized, phasecorr, phasecorrdirection, dzcorr);
      }
      /*if (EQ) {
        dropped[j] = true;
      }
      if (labelEQ) {
        droppedMC[j] = true;
        histMatch[CAMath::Min<int32_t>(100, d * 10.f)]++;
      }
      if (d < 10.f && !labelEQ) {
        histFail[CAMath::Min<int32_t>(100, d * 10.f)]++;
    }*/
#endif
      if (EQ) {
        mOutputTracks[params[j].id].SetMergedLooper(true);
        if (CAMath::Abs(param2.GetQPt() * Param().qptB5Scaler) >= Param().rec.tpc.rejectQPtB5) {
          mOutputTracks[params[i].id].SetMergedLooper(true);
        }
      }
    }
  }
  /*#if GPUCA_MERGE_LOOPER_MC && !defined(GPUCA_GPUCODE)
  int32_t total = 0, totalmc = 0, good = 0, missed = 0, fake = 0;
  for (uint32_t i = 0; i < mMemory->nLooperMatchCandidates; i++) {
    total += dropped[i];
    totalmc += droppedMC[i];
    good += dropped[i] && droppedMC[i];
    missed += droppedMC[i] && !dropped[i];
    fake += dropped[i] && !droppedMC[i];
  }
  if (good) {
    printf("%20s: %8d\n", "Total", total);
    printf("%20s: %8d\n", "TotalMC", totalmc);
    printf("%20s: %8d (%8.3f%% %8.3f%%)\n", "Good", good, 100.f * good / total, 100.f * good / totalmc);
    printf("%20s: %8d (%8.3f%%)\n", "Missed", missed, 100.f * missed / totalmc);
    printf("%20s: %8d (%8.3f%%)\n", "Fake", fake, 100.f * fake / total);
  }
  printf("Match histo\n");
  for (uint32_t i = 0; i < histMatch.size(); i++) {
    printf("%8.3f: %3d\n", i / 10.f + 0.05f, histMatch[i]);
  }
  printf("Fake histo\n");
  for (uint32_t i = 0; i < histFail.size(); i++) {
    printf("%8.3f: %3d\n", i / 10.f + 0.05f, histFail[i]);
  }
#endif*/
}