@c -*-texinfo-*- @c This file is part of the StarPU Handbook. @c Copyright (C) 2009--2011 Universit@'e de Bordeaux 1 @c Copyright (C) 2010, 2011, 2012 Centre National de la Recherche Scientifique @c Copyright (C) 2011, 2012 Institut National de Recherche en Informatique et Automatique @c See the file starpu.texi for copying conditions. @menu * Compilation configuration:: * Execution configuration through environment variables:: @end menu @node Compilation configuration @section Compilation configuration The following arguments can be given to the @code{configure} script. @menu * Common configuration:: * Configuring workers:: * Extension configuration:: * Advanced configuration:: @end menu @node Common configuration @subsection Common configuration @table @code @item --enable-debug Enable debugging messages. @item --enable-fast Disable assertion checks, which saves computation time. @item --enable-verbose Increase the verbosity of the debugging messages. This can be disabled at runtime by setting the environment variable @code{STARPU_SILENT} to any value. @smallexample % STARPU_SILENT=1 ./vector_scal @end smallexample @item --enable-coverage Enable flags for the @code{gcov} coverage tool. @end table @node Configuring workers @subsection Configuring workers @table @code @item --enable-maxcpus=@var{count} Use at most @var{count} CPU cores. This information is then available as the @code{STARPU_MAXCPUS} macro. @item --disable-cpu Disable the use of CPUs of the machine. Only GPUs etc. will be used. @item --enable-maxcudadev=@var{count} Use at most @var{count} CUDA devices. This information is then available as the @code{STARPU_MAXCUDADEVS} macro. @item --disable-cuda Disable the use of CUDA, even if a valid CUDA installation was detected. @item --with-cuda-dir=@var{prefix} Search for CUDA under @var{prefix}, which should notably contain @file{include/cuda.h}. @item --with-cuda-include-dir=@var{dir} Search for CUDA headers under @var{dir}, which should notably contain @code{cuda.h}. This defaults to @code{/include} appended to the value given to @code{--with-cuda-dir}. @item --with-cuda-lib-dir=@var{dir} Search for CUDA libraries under @var{dir}, which should notably contain the CUDA shared libraries---e.g., @file{libcuda.so}. This defaults to @code{/lib} appended to the value given to @code{--with-cuda-dir}. @item --disable-cuda-memcpy-peer Explicitly disable peer transfers when using CUDA 4.0. @item --enable-maxopencldev=@var{count} Use at most @var{count} OpenCL devices. This information is then available as the @code{STARPU_MAXOPENCLDEVS} macro. @item --disable-opencl Disable the use of OpenCL, even if the SDK is detected. @item --with-opencl-dir=@var{prefix} Search for an OpenCL implementation under @var{prefix}, which should notably contain @file{include/CL/cl.h} (or @file{include/OpenCL/cl.h} on Mac OS). @item --with-opencl-include-dir=@var{dir} Search for OpenCL headers under @var{dir}, which should notably contain @file{CL/cl.h} (or @file{OpenCL/cl.h} on Mac OS). This defaults to @code{/include} appended to the value given to @code{--with-opencl-dir}. @item --with-opencl-lib-dir=@var{dir} Search for an OpenCL library under @var{dir}, which should notably contain the OpenCL shared libraries---e.g. @file{libOpenCL.so}. This defaults to @code{/lib} appended to the value given to @code{--with-opencl-dir}. @item --enable-gordon Enable the use of the Gordon runtime for Cell SPUs. @c TODO: rather default to enabled when detected @item --with-gordon-dir=@var{prefix} Search for the Gordon SDK under @var{prefix}. @item --enable-maximplementations=@var{count} Allow for at most @var{count} codelet implementations for the same target device. This information is then available as the @code{STARPU_MAXIMPLEMENTATIONS} macro. @end table @node Extension configuration @subsection Extension configuration @table @code @item --disable-socl Disable the SOCL extension (@pxref{SOCL OpenCL Extensions}). By default, it is enabled when an OpenCL implementation is found. @item --disable-starpu-top Disable the StarPU-Top interface (@pxref{StarPU-Top}). By default, it is enabled when the required dependencies are found. @item --disable-gcc-extensions Disable the GCC plug-in (@pxref{C Extensions}). By default, it is enabled when the GCC compiler provides a plug-in support. @item --with-mpicc=@var{path} Use the @command{mpicc} compiler at @var{path}, for starpumpi (@pxref{StarPU MPI support}). @item --enable-comm-stats Enable communication statistics for starpumpi (@pxref{StarPU MPI support}). @end table @node Advanced configuration @subsection Advanced configuration @table @code @item --enable-perf-debug Enable performance debugging through gprof. @item --enable-model-debug Enable performance model debugging. @item --enable-stats @c see ../../src/datawizard/datastats.c Enable gathering of memory transfer statistics. @item --enable-maxbuffers Define the maximum number of buffers that tasks will be able to take as parameters, then available as the @code{STARPU_NMAXBUFS} macro. @item --enable-allocation-cache Enable the use of a data allocation cache to avoid the cost of it with CUDA. Still experimental. @item --enable-opengl-render Enable the use of OpenGL for the rendering of some examples. @c TODO: rather default to enabled when detected @item --enable-blas-lib Specify the blas library to be used by some of the examples. The library has to be 'atlas' or 'goto'. @item --disable-starpufft Disable the build of libstarpufft, even if fftw or cuFFT is available. @item --with-magma=@var{prefix} Search for MAGMA under @var{prefix}. @var{prefix} should notably contain @file{include/magmablas.h}. @item --with-fxt=@var{prefix} Search for FxT under @var{prefix}. @url{http://savannah.nongnu.org/projects/fkt, FxT} is used to generate traces of scheduling events, which can then be rendered them using ViTE (@pxref{Off-line, off-line performance feedback}). @var{prefix} should notably contain @code{include/fxt/fxt.h}. @item --with-perf-model-dir=@var{dir} Store performance models under @var{dir}, instead of the current user's home. @item --with-goto-dir=@var{prefix} Search for GotoBLAS under @var{prefix}. @item --with-atlas-dir=@var{prefix} Search for ATLAS under @var{prefix}, which should notably contain @file{include/cblas.h}. @item --with-mkl-cflags=@var{cflags} Use @var{cflags} to compile code that uses the MKL library. @item --with-mkl-ldflags=@var{ldflags} Use @var{ldflags} when linking code that uses the MKL library. Note that the @url{http://software.intel.com/en-us/articles/intel-mkl-link-line-advisor/, MKL website} provides a script to determine the linking flags. @end table @node Execution configuration through environment variables @section Execution configuration through environment variables @menu * Workers:: Configuring workers * Scheduling:: Configuring the Scheduling engine * Misc:: Miscellaneous and debug @end menu @node Workers @subsection Configuring workers @menu * STARPU_NCPU:: Number of CPU workers * STARPU_NCUDA:: Number of CUDA workers * STARPU_NOPENCL:: Number of OpenCL workers * STARPU_NGORDON:: Number of SPU workers (Cell) * STARPU_WORKERS_NOBIND:: Do not bind workers * STARPU_WORKERS_CPUID:: Bind workers to specific CPUs * STARPU_WORKERS_CUDAID:: Select specific CUDA devices * STARPU_WORKERS_OPENCLID:: Select specific OpenCL devices * STARPU_SINGLE_COMBINED_WORKER:: Do not use concurrent workers * STARPU_MIN_WORKERSIZE:: Minimum size of the combined workers * STARPU_MAX_WORKERSIZE:: Maximum size of the combined workers @end menu @node STARPU_NCPU @subsubsection @code{STARPU_NCPU} -- Number of CPU workers Specify the number of CPU workers (thus not including workers dedicated to control acceleratores). Note that by default, StarPU will not allocate more CPU workers than there are physical CPUs, and that some CPUs are used to control the accelerators. @node STARPU_NCUDA @subsubsection @code{STARPU_NCUDA} -- Number of CUDA workers Specify the number of CUDA devices that StarPU can use. If @code{STARPU_NCUDA} is lower than the number of physical devices, it is possible to select which CUDA devices should be used by the means of the @code{STARPU_WORKERS_CUDAID} environment variable. By default, StarPU will create as many CUDA workers as there are CUDA devices. @node STARPU_NOPENCL @subsubsection @code{STARPU_NOPENCL} -- Number of OpenCL workers OpenCL equivalent of the @code{STARPU_NCUDA} environment variable. @node STARPU_NGORDON @subsubsection @code{STARPU_NGORDON} -- Number of SPU workers (Cell) Specify the number of SPUs that StarPU can use. @node STARPU_WORKERS_NOBIND @subsubsection @code{STARPU_WORKERS_NOBIND} -- Do not bind workers to specific CPUs Setting it to non-zero will prevent StarPU from binding its threads to CPUs. This is for instance useful when running the testsuite in parallel. @node STARPU_WORKERS_CPUID @subsubsection @code{STARPU_WORKERS_CPUID} -- Bind workers to specific CPUs Passing an array of integers (starting from 0) in @code{STARPU_WORKERS_CPUID} specifies on which logical CPU the different workers should be bound. For instance, if @code{STARPU_WORKERS_CPUID = "0 1 4 5"}, the first worker will be bound to logical CPU #0, the second CPU worker will be bound to logical CPU #1 and so on. Note that the logical ordering of the CPUs is either determined by the OS, or provided by the @code{hwloc} library in case it is available. Note that the first workers correspond to the CUDA workers, then come the OpenCL and the SPU, and finally the CPU workers. For example if we have @code{STARPU_NCUDA=1}, @code{STARPU_NOPENCL=1}, @code{STARPU_NCPU=2} and @code{STARPU_WORKERS_CPUID = "0 2 1 3"}, the CUDA device will be controlled by logical CPU #0, the OpenCL device will be controlled by logical CPU #2, and the logical CPUs #1 and #3 will be used by the CPU workers. If the number of workers is larger than the array given in @code{STARPU_WORKERS_CPUID}, the workers are bound to the logical CPUs in a round-robin fashion: if @code{STARPU_WORKERS_CPUID = "0 1"}, the first and the third (resp. second and fourth) workers will be put on CPU #0 (resp. CPU #1). This variable is ignored if the @code{use_explicit_workers_bindid} flag of the @code{starpu_conf} structure passed to @code{starpu_init} is set. @node STARPU_WORKERS_CUDAID @subsubsection @code{STARPU_WORKERS_CUDAID} -- Select specific CUDA devices Similarly to the @code{STARPU_WORKERS_CPUID} environment variable, it is possible to select which CUDA devices should be used by StarPU. On a machine equipped with 4 GPUs, setting @code{STARPU_WORKERS_CUDAID = "1 3"} and @code{STARPU_NCUDA=2} specifies that 2 CUDA workers should be created, and that they should use CUDA devices #1 and #3 (the logical ordering of the devices is the one reported by CUDA). This variable is ignored if the @code{use_explicit_workers_cuda_gpuid} flag of the @code{starpu_conf} structure passed to @code{starpu_init} is set. @node STARPU_WORKERS_OPENCLID @subsubsection @code{STARPU_WORKERS_OPENCLID} -- Select specific OpenCL devices OpenCL equivalent of the @code{STARPU_WORKERS_CUDAID} environment variable. This variable is ignored if the @code{use_explicit_workers_opencl_gpuid} flag of the @code{starpu_conf} structure passed to @code{starpu_init} is set. @node STARPU_SINGLE_COMBINED_WORKER @subsubsection @code{STARPU_SINGLE_COMBINED_WORKER} -- Do not use concurrent workers If set, StarPU will create several workers which won't be able to work concurrently. It will create combined workers which size goes from 1 to the total number of CPU workers in the system. @node STARPU_MIN_WORKERSIZE @subsubsection @code{STARPU_MIN_WORKERSIZE} -- Minimum size of the combined workers Let the user give a hint to StarPU about which how many workers (minimum boundary) the combined workers should contain. @node STARPU_MAX_WORKERSIZE @subsubsection @code{STARPU_MAX_WORKERSIZE} -- Maximum size of the combined workers Let the user give a hint to StarPU about which how many workers (maximum boundary) the combined workers should contain. @node Scheduling @subsection Configuring the Scheduling engine @menu * STARPU_SCHED:: Scheduling policy * STARPU_CALIBRATE:: Calibrate performance models * STARPU_PREFETCH:: Use data prefetch * STARPU_SCHED_ALPHA:: Computation factor * STARPU_SCHED_BETA:: Communication factor @end menu @node STARPU_SCHED @subsubsection @code{STARPU_SCHED} -- Scheduling policy Choose between the different scheduling policies proposed by StarPU: work random, stealing, greedy, with performance models, etc. Use @code{STARPU_SCHED=help} to get the list of available schedulers. @node STARPU_CALIBRATE @subsubsection @code{STARPU_CALIBRATE} -- Calibrate performance models If this variable is set to 1, the performance models are calibrated during the execution. If it is set to 2, the previous values are dropped to restart calibration from scratch. Setting this variable to 0 disable calibration, this is the default behaviour. Note: this currently only applies to @code{dm}, @code{dmda} and @code{heft} scheduling policies. @node STARPU_PREFETCH @subsubsection @code{STARPU_PREFETCH} -- Use data prefetch This variable indicates whether data prefetching should be enabled (0 means that it is disabled). If prefetching is enabled, when a task is scheduled to be executed e.g. on a GPU, StarPU will request an asynchronous transfer in advance, so that data is already present on the GPU when the task starts. As a result, computation and data transfers are overlapped. Note that prefetching is enabled by default in StarPU. @node STARPU_SCHED_ALPHA @subsubsection @code{STARPU_SCHED_ALPHA} -- Computation factor To estimate the cost of a task StarPU takes into account the estimated computation time (obtained thanks to performance models). The alpha factor is the coefficient to be applied to it before adding it to the communication part. @node STARPU_SCHED_BETA @subsubsection @code{STARPU_SCHED_BETA} -- Communication factor To estimate the cost of a task StarPU takes into account the estimated data transfer time (obtained thanks to performance models). The beta factor is the coefficient to be applied to it before adding it to the computation part. @node Misc @subsection Miscellaneous and debug @menu * STARPU_SILENT:: Disable verbose mode * STARPU_LOGFILENAME:: Select debug file name * STARPU_FXT_PREFIX:: FxT trace location * STARPU_LIMIT_GPU_MEM:: Restrict memory size on the GPUs * STARPU_GENERATE_TRACE:: Generate a Paje trace when StarPU is shut down @end menu @node STARPU_SILENT @subsubsection @code{STARPU_SILENT} -- Disable verbose mode This variable allows to disable verbose mode at runtime when StarPU has been configured with the option @code{--enable-verbose}. @node STARPU_LOGFILENAME @subsubsection @code{STARPU_LOGFILENAME} -- Select debug file name This variable specifies in which file the debugging output should be saved to. @node STARPU_FXT_PREFIX @subsubsection @code{STARPU_FXT_PREFIX} -- FxT trace location This variable specifies in which directory to save the trace generated if FxT is enabled. It needs to have a trailing '/' character. @node STARPU_LIMIT_GPU_MEM @subsubsection @code{STARPU_LIMIT_GPU_MEM} -- Restrict memory size on the GPUs This variable specifies the maximum number of megabytes that should be available to the application on each GPUs. In case this value is smaller than the size of the memory of a GPU, StarPU pre-allocates a buffer to waste memory on the device. This variable is intended to be used for experimental purposes as it emulates devices that have a limited amount of memory. @node STARPU_GENERATE_TRACE @subsubsection @code{STARPU_GENERATE_TRACE} -- Generate a Paje trace when StarPU is shut down When set to 1, this variable indicates that StarPU should automatically generate a Paje trace when starpu_shutdown is called.