customizePixelOnlyForProfiling Namespace Reference

Functions
def	customizePixelOnlyForProfiling (process)
def	customizePixelOnlyForProfilingGPUOnly (process)
def	customizePixelOnlyForProfilingGPUWithHostCopy (process)

Function Documentation

customizePixelOnlyForProfiling()

def customizePixelOnlyForProfiling.customizePixelOnlyForProfiling

(

process

)

Definition at line 49 of file customizePixelOnlyForProfiling.py.

def customizePixelOnlyForProfiling(process):

  process.consumer = cms.EDAnalyzer("GenericConsumer",
      eventProducts = cms.untracked.vstring('pixelTracks', 'pixelVertices')
  )

  process.consume_step = cms.EndPath(process.consumer)

  process.schedule = cms.Schedule(process.raw2digi_step, process.reconstruction_step, process.consume_step)

  return process

customizePixelOnlyForProfilingGPUOnly()

def customizePixelOnlyForProfiling.customizePixelOnlyForProfilingGPUOnly

(

process

)

Definition at line 8 of file customizePixelOnlyForProfiling.py.

def customizePixelOnlyForProfilingGPUOnly(process):

  process.consumer = cms.EDAnalyzer("GenericConsumer",
      eventProducts = cms.untracked.vstring('pixelTracksCUDA', 'pixelVerticesCUDA', '*DeviceProduct_pixelTracksAlpaka_*_*', '*DeviceProduct_pixelVerticesAlpaka_*_*')
  )

  process.consume_step = cms.EndPath(process.consumer)

  process.schedule = cms.Schedule(process.raw2digi_step, process.reconstruction_step, process.consume_step)

  return process


# Customise the Pixel-only reconstruction to run on GPU, and copy the data to the host
#
# Run the unpacker, clustering, ntuplets, track fit and vertex reconstruction on GPU,
# and copy all the products to the host in SoA format.
#
# The same customisation can be also used on the SoA CPU workflow, running up to the
# tracks and vertices on the CPU in SoA format, without conversion to legacy format.

customizePixelOnlyForProfilingGPUWithHostCopy()

def customizePixelOnlyForProfiling.customizePixelOnlyForProfilingGPUWithHostCopy

(

process

)

Definition at line 28 of file customizePixelOnlyForProfiling.py.

def customizePixelOnlyForProfilingGPUWithHostCopy(process):

  process.consumer = cms.EDAnalyzer("GenericConsumer",
      eventProducts = cms.untracked.vstring('pixelTracksSoA', 'pixelVerticesSoA', 'pixelTracksAlpaka', 'pixelVerticesAlpaka')
  )

  process.consume_step = cms.EndPath(process.consumer)

  process.schedule = cms.Schedule(process.raw2digi_step, process.reconstruction_step, process.consume_step)

  return process


# Customise the Pixel-only reconstruction to run on GPU, copy the data to the host,
# and convert to legacy format
#
# Run the unpacker, clustering, ntuplets, track fit and vertex reconstruction on GPU;
# copy all the products to the host in SoA format; and convert them to legacy format.
#
# The same customisation can be also used on the CPU workflow, running up to the
# tracks and vertices on the CPU.

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