• Introduction
• Status
• Quick recipe
  • Additional make targets
  • Test program specific notes (if any)
    • fwtest
    • cuda
    • cudadev
    • cudauvm
    • kokkos and kokkostest
• Code structure
• Build system
• Contribution guide

The purpose of this package is to explore various performance portability solutions with the Patatrack pixel tracking application. The version here corresponds to CMSSW_11_2_0_pre8_Patatrack.

The application is designed to require minimal dependencies on the system. All programs require

• GNU Make, curl, md5sum, tar
• C++17 capable compiler. Ffor programs using CUDA that must work with nvcc, in the current setup this means GCC 8 or 9, possibly 10 with CUDA 11.1
  • testing is currently done with GCC 8

In addition, the individual programs assume the following be found from the system

All other dependencies (listed below) are downloaded and built automatically

• (*) Boost libraries from the system can also be used, but they need to be newer than 1.65.1

The input data set consists of a minimal binary dump of 1000 events of ttbar+PU events from of /TTToHadronic_TuneCP5_13TeV-powheg-pythia8/RunIIAutumn18DR-PUAvg50IdealConditions_IdealConditions_102X_upgrade2018_design_v9_ext1-v2/FEVTDEBUGHLT dataset from the CMS Open Data. The data are downloaded automatically during the build process.

The "Device framework" refers to a mechanism similar to cms::cuda::Product and cms::cuda::ScopedContext to support chains of modules to use the same device and the same work queue.

The column "Validated" means that the program produces the same histograms as the reference cuda program within numerical precision (judged "by eye").

# Build application with N-fold concurrency
$ make -j N cuda

# For CUDA installations elsewhere than /usr/local/cuda
$ make -j N cuda CUDA_BASE=/path/to/cuda

# Source environment
$ source env.sh

# Process 1000 events in 1 thread
$ ./cuda

# Command line arguments
$ ./cuda -h
./cuda: [--numberOfThreads NT] [--numberOfStreams NS] [--maxEvents ME] [--data PATH] [--transfer] [--validation] [--empty]

Options
 --numberOfThreads   Number of threads to use (default 1)
 --numberOfStreams   Number of concurrent events (default 0=numberOfThreads)
 --maxEvents         Number of events to process (default -1 for all events in the input file)
 --data              Path to the 'data' directory (default 'data' in the directory of the executable)
 --transfer          Transfer results from GPU to CPU (default is to leave them on GPU)
 --validation        Run (rudimentary) validation at the end (implies --transfer)
 --empty             Ignore all producers (for testing only)

Note that the contents of all, test, and all test_<arch> targets are filtered based on the availability of compilers/toolchains. Essentially

• by default programs using only GCC (or "host compiler") are included
• if CUDA_BASE directory exists, programs using CUDA are included
• if SYCL_BASE directory exists, programs using SYCL are included

The printouts can be disabled with -DFWTEST_SILENT build flag (e.g. make ... USER_CXXFLAGS="-DFWTEST_SILENT").

This program is frozen to correspond to CMSSW_11_2_0_pre8_Patatrack.

This program is currently equivalent to cuda.

The purpose of this program is to test the performance of the CUDA managed memory. There are various macros that can be used to switch on and off various behaviors. The default behavior is to use use managed memory only for those memory blocks that are used for memory transfers, call cudaMemPrefetchAsync(), and cudaMemAdvise(cudaMemAdviseSetReadMostly). The macros can be set at compile time along

make cudauvm ... USER_CXXFLAGS="-DCUDAUVM_DISABLE_ADVISE"

To use managed memory also for temporary device-only allocations, compile with

make cudauvm ... USER_CXXFLAGS="-DCUDAUVM_MANAGED_TEMPORARY"

# If nvcc is not in $PATH, create environment file and source it
$ make environment [CUDA_BASE=...]
$ source env.sh

# Actual build command
$ make -j N kokkos [CUDA_BASE=...] [KOKKOS_CUDA_ARCH=...] [...]
$ ./kokkos --cuda

# If changing KOKKOS_HOST_PARALLEL or KOKKOS_DEVICE_PARALLEL, clean up existing build first
$ make clean external_kokkos_clean
$ make kokkos ...

• Note that if CUDA_BASE needs to be set, it needs to be set for both make commands.
• The target CUDA architecture needs to be set explicitly with KOKKOS_CUDA_ARCH
  • Default value is 70 (7.0) for Volta
  • Other accepted values are 75 (Turing), the list can be extended as neeeded
• The CMake executable can be set with CMAKE in case the default one is too old.
• The backends to be used in the Kokkos runtime library build are set with KOKKOS_HOST_PARALLEL and KOKKOS_DEVICE_PARALLEL (see table below)
  • The Serial backend is always enabled
• When running, the backend(s) need to be set explicitly via command line parameters
  • --serial for CPU serial backend
  • --pthread for CPU pthread backend
  • --cuda for CUDA backend
• Use of multiple threads (--numberOfThreads) has not been tested and likely does not work correctly. Concurrent events (--numberOfStreams) works.

The project is split into several programs, one (or more) for each test case. Each test case has its own directory under src directory. A test case contains the full application: framework, data formats, device tooling, plugins for the algorithmic modules ran by the framework, and the executable.

Each test program is structured as follows within src/<program name> (examples point to cuda

• Makefile that defines the actual build rules for the program
• Makefile.deps that declares the external dependencies of the program, and the dependencies between shared objects within the program
• plugins.txt contains a simple mapping from module names to the plugin shared object names
  • In CMSSW such information is generated automatically by scram, in this project the original author was lazy to automate that
• bin/ directory that contains all the framework code for the executable binary. These files should not need to be modified, except main.cc for changin the set of modules to run, and possibly more command line options
• plugin-<PluginName>/ directories contain the source code for plugins. The <PluginName> part specifies the name of the plugin, and the resulting shared object file is plugin<PluginName>.so. Note that no other library or plugin may depend on a plugin (either at link time or even thourgh #including a header). The plugins may only be loaded through the names of the modules by the PluginManager.
• <LibraryName>/: the remaining directories are for libraries. The <LibraryName> specifies the name of the library, and the resulting shared object file is lib<LibraryName>.so. Other libraries or plugins may depend on a library, in which case the dependence must be declared in Makefile.deps.
  • CondFormats/:
  • CUDADataFormats/: CUDA-specific data structures that can be passed from one module to another via the edm::Event. A given portability technology likely needs its own data format directory, the CUDADataFormats can be used as an example.
  • CUDACore/: Various tools for CUDA. A given portability technology likely needs its own tool directory, the CUDACore can be used as an example.
  • DataFormats/: mainly CPU-side data structures that can be passed from one module to another via the edm::Event. Some of these are produced by the edm::Source by reading the binary dumps. These files should not need to be modified. New classes may be added, but they should be independent of the portability technology.
  • Framework/: crude approximation of the CMSSW framework. Utilizes TBB tasks to orchestrate the processing of the events by the modules. These files should not need to be modified.
  • Geometry/: geometry information, essentially handful of compile-time constants. May be modified.

For more detailed description of the application structure (mostly plugins) see CodeStructure.md

The build system is based on pure GNU Make. There are two levels of Makefiles. The top-level Makefile handles the building of the entire project: it defines general build flags, paths to external dependencies in the system, recipes to download and build the externals, and targets for the test programs.

For more information see BuildSystem.md.

Given that the approach of this project is to maintain many programs in a single branch, in order to keep the commit history readable, each commit should contain changes only for one test program, and the short commit message should start with the program name, e.g. [cuda]. A pull request may touch many test programs. General commits (e.g. top-level Makefile or documentation) can be left without such a prefix.

When starting work for a new portability technology, the first steps are to figure out the installation of the necessary external software packages and the build rules (both can be adjusted later). It is probably best to start by cloning the fwtest code for the new program (e.g. footest for a technology foo), adjust the test modules to exercise the API of the technology (see cudatest for examples), and start crafting the tools package (CUDACore in cuda).

Pull requests are expected to build (make all succeeds) and pass tests (make test). Programs to have build errors should primarily be filtered out from $(TARGETS), and failing tests should primarily be removed from the set of tests run by default. Breakages can, however, be accepted for short periods of time with a good justification.