starpu-max/doc/doxygen/chapters/501_environment_variables.doxy

/* StarPU --- Runtime system for heterogeneous multicore architectures.
 *
 * Copyright (C) 2011-2013,2015-2017                      Inria
 * Copyright (C) 2010-2018                                CNRS
 * Copyright (C) 2009-2011,2013-2017                      Université de Bordeaux
 * Copyright (C) 2016                                     Uppsala University
 *
 * StarPU is free software; you can redistribute it and/or modify
 * it under the terms of the GNU Lesser General Public License as published by
 * the Free Software Foundation; either version 2.1 of the License, or (at
 * your option) any later version.
 *
 * StarPU is distributed in the hope that it will be useful, but
 * WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
 *
 * See the GNU Lesser General Public License in COPYING.LGPL for more details.
 */

/*! \page ExecutionConfigurationThroughEnvironmentVariables Execution Configuration Through Environment Variables

The behavior of the StarPU library and tools may be tuned thanks to
the following environment variables.

\section ConfiguringWorkers Configuring Workers

<dl>

<dt>STARPU_NCPU</dt>
<dd>
\anchor STARPU_NCPU
\addindex __env__STARPU_NCPU
Specify the number of CPU workers (thus not including workers
dedicated to control accelerators). 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.
</dd>

<dt>STARPU_NCPUS</dt>
<dd>
\anchor STARPU_NCPUS
\addindex __env__STARPU_NCPUS
This variable is deprecated. You should use \ref STARPU_NCPU.
</dd>

<dt>STARPU_NCUDA</dt>
<dd>
\anchor STARPU_NCUDA
\addindex __env__STARPU_NCUDA
Specify the number of CUDA devices that StarPU can use. If
\ref 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
environment variable \ref STARPU_WORKERS_CUDAID. By default, StarPU will
create as many CUDA workers as there are CUDA devices.
</dd>

<dt>STARPU_NWORKER_PER_CUDA</dt>
<dd>
\anchor STARPU_NWORKER_PER_CUDA
\addindex __env__STARPU_NWORKER_PER_CUDA
Specify the number of workers per CUDA device, and thus the number of kernels
which will be concurrently running on the devices. The default value is 1.
</dd>

<dt>STARPU_CUDA_THREAD_PER_WORKER</dt>
<dd>
\anchor STARPU_CUDA_THREAD_PER_WORKER
\addindex __env__STARPU_CUDA_THREAD_PER_WORKER
Specify if the cuda driver should provide a thread per stream or a single thread
dealing with all the streams. 0 if one thread per stream, 1 otherwise. The default
value is 0. Setting it to 1 is contradictory with setting STARPU_CUDA_THREAD_PER_DEV to 1.
</dd>

<dt>STARPU_CUDA_THREAD_PER_DEV</dt>
<dd>
\anchor STARPU_CUDA_THREAD_PER_DEV
\addindex __env__STARPU_CUDA_THREAD_PER_DEV
Specify if the cuda driver should provide a thread per device or a single thread
dealing with all the devices. 0 if one thread per device, 1 otherwise. The default
value is 1, unless STARPU_CUDA_THREAD_PER_WORKER is set to 1. Setting it to 1 is
contradictory with setting STARPU_CUDA_THREAD_PER_WORKER to 1.
</dd>

<dt>STARPU_CUDA_PIPELINE</dt>
<dd>
\anchor STARPU_CUDA_PIPELINE
\addindex __env__STARPU_CUDA_PIPELINE
Specify how many asynchronous tasks are submitted in advance on CUDA
devices. This for instance permits to overlap task management with the execution
of previous tasks, but it also allows concurrent execution on Fermi cards, which
otherwise bring spurious synchronizations. The default is 2. Setting the value to 0 forces a synchronous
execution of all tasks.
</dd>

<dt>STARPU_NOPENCL</dt>
<dd>
\anchor STARPU_NOPENCL
\addindex __env__STARPU_NOPENCL
OpenCL equivalent of the environment variable \ref STARPU_NCUDA.
</dd>

<dt>STARPU_OPENCL_PIPELINE</dt>
<dd>
\anchor STARPU_OPENCL_PIPELINE
\addindex __env__STARPU_OPENCL_PIPELINE
Specify how many asynchronous tasks are submitted in advance on OpenCL
devices. This for instance permits to overlap task management with the execution
of previous tasks, but it also allows concurrent execution on Fermi cards, which
otherwise bring spurious synchronizations. The default is 2. Setting the value to 0 forces a synchronous
execution of all tasks.
</dd>

<dt>STARPU_OPENCL_ON_CPUS</dt>
<dd>
\anchor STARPU_OPENCL_ON_CPUS
\addindex __env__STARPU_OPENCL_ON_CPUS
By default, the OpenCL driver only enables GPU and accelerator
devices. By setting the environment variable \ref STARPU_OPENCL_ON_CPUS
to 1, the OpenCL driver will also enable CPU devices.
</dd>

<dt>STARPU_OPENCL_ONLY_ON_CPUS</dt>
<dd>
\anchor STARPU_OPENCL_ONLY_ON_CPUS
\addindex __env__STARPU_OPENCL_ONLY_ON_CPUS
By default, the OpenCL driver enables GPU and accelerator
devices. By setting the environment variable \ref STARPU_OPENCL_ONLY_ON_CPUS
to 1, the OpenCL driver will ONLY enable CPU devices.
</dd>

<dt>STARPU_NMIC</dt>
<dd>
\anchor STARPU_NMIC
\addindex __env__STARPU_NMIC
MIC equivalent of the environment variable \ref STARPU_NCUDA, i.e. the number of
MIC devices to use.
</dd>

<dt>STARPU_NMICTHREADS</dt>
<dd>
\anchor STARPU_NMICTHREADS
\addindex __env__STARPU_NMICTHREADS
Number of threads to use on the MIC devices.
</dd>

<dt>STARPU_NMPI_MS</dt>
<dd>
\anchor STARPU_NMPI_MS
\addindex __env__STARPU_NMPI_MS
MPI Master Slave equivalent of the environment variable \ref STARPU_NCUDA, i.e. the number of
MPI Master Slave devices to use.
</dd>

<dt>STARPU_NMPIMSTHREADS</dt>
<dd>
\anchor STARPU_NMPIMSTHREADS
\addindex __env__STARPU_NMPIMSTHREADS
Number of threads to use on the MPI Slave devices.
</dd>

<dt>STARPU_MPI_MASTER_NODE</dt>
<dd>
\anchor STARPU_MPI_MASTER_NODE
\addindex __env__STARPU_MPI_MASTER_NODE
This variable allows to chose which MPI node (with the MPI ID) will be the master.
</dd>

<dt>STARPU_NSCC</dt>
<dd>
\anchor STARPU_NSCC
\addindex __env__STARPU_NSCC
SCC equivalent of the environment variable \ref STARPU_NCUDA.
</dd>

<dt>STARPU_WORKERS_NOBIND</dt>
<dd>
\anchor STARPU_WORKERS_NOBIND
\addindex __env__STARPU_WORKERS_NOBIND
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.
</dd>

<dt>STARPU_WORKERS_CPUID</dt>
<dd>
\anchor STARPU_WORKERS_CPUID
\addindex __env__STARPU_WORKERS_CPUID
Passing an array of integers in \ref STARPU_WORKERS_CPUID
specifies on which logical CPU the different workers should be
bound. For instance, if <c>STARPU_WORKERS_CPUID = "0 1 4 5"</c>, 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 library <c>hwloc</c> in case it is
available. Ranges can be provided: for instance, <c>STARPU_WORKERS_CPUID = "1-3
5"</c> will bind the first three workers on logical CPUs #1, #2, and #3, and the
fourth worker on logical CPU #5. Unbound ranges can also be provided:
<c>STARPU_WORKERS_CPUID = "1-"</c> will bind the workers starting from logical
CPU #1 up to last CPU.

Note that the first workers correspond to the CUDA workers, then come the
OpenCL workers, and finally the CPU workers. For example if
we have <c>STARPU_NCUDA=1</c>, <c>STARPU_NOPENCL=1</c>, <c>STARPU_NCPU=2</c>
and <c>STARPU_WORKERS_CPUID = "0 2 1 3"</c>, 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
\ref STARPU_WORKERS_CPUID, the workers are bound to the logical CPUs in a
round-robin fashion: if <c>STARPU_WORKERS_CPUID = "0 1"</c>, 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 field
starpu_conf::use_explicit_workers_bindid passed to starpu_init() is
set.

</dd>

<dt>STARPU_MAIN_THREAD_CPUID</dt>
<dd>
\anchor STARPU_MAIN_THREAD_CPUID
\addindex __env__STARPU_MAIN_THREAD_CPUID
When defined, this make StarPU bind the thread that calls starpu_initialize() to
the given CPU ID.
</dd>

<dt>STARPU_MPI_THREAD_CPUID</dt>
<dd>
\anchor STARPU_MPI_THREAD_CPUID
\addindex __env__STARPU_MPI_THREAD_CPUID
When defined, this make StarPU bind its MPI thread to the given CPU ID.
</dd>

<dt>STARPU_WORKERS_CUDAID</dt>
<dd>
\anchor STARPU_WORKERS_CUDAID
\addindex __env__STARPU_WORKERS_CUDAID
Similarly to the \ref 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 <c>STARPU_WORKERS_CUDAID = "1 3"</c> and
<c>STARPU_NCUDA=2</c> 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 field
starpu_conf::use_explicit_workers_cuda_gpuid passed to starpu_init()
is set.
</dd>

<dt>STARPU_WORKERS_OPENCLID</dt>
<dd>
\anchor STARPU_WORKERS_OPENCLID
\addindex __env__STARPU_WORKERS_OPENCLID
OpenCL equivalent of the \ref STARPU_WORKERS_CUDAID environment variable.

This variable is ignored if the field
starpu_conf::use_explicit_workers_opencl_gpuid passed to starpu_init()
is set.
</dd>

<dt>STARPU_WORKERS_MICID</dt>
<dd>
\anchor STARPU_WORKERS_MICID
\addindex __env__STARPU_WORKERS_MICID
MIC equivalent of the \ref STARPU_WORKERS_CUDAID environment variable.

This variable is ignored if the field
starpu_conf::use_explicit_workers_mic_deviceid passed to starpu_init()
is set.
</dd>

<dt>STARPU_WORKERS_SCCID</dt>
<dd>
\anchor STARPU_WORKERS_SCCID
\addindex __env__STARPU_WORKERS_SCCID
SCC equivalent of the \ref STARPU_WORKERS_CUDAID environment variable.

This variable is ignored if the field
starpu_conf::use_explicit_workers_scc_deviceid passed to starpu_init()
is set.
</dd>

<dt>STARPU_WORKER_TREE</dt>
<dd>
\anchor STARPU_WORKER_TREE
\addindex __env__STARPU_WORKER_TREE
Define to 1 to enable the tree iterator in schedulers.
</dd>

<dt>STARPU_SINGLE_COMBINED_WORKER</dt>
<dd>
\anchor STARPU_SINGLE_COMBINED_WORKER
\addindex __env__STARPU_SINGLE_COMBINED_WORKER
If set, StarPU will create several workers which won't be able to work
concurrently. It will by default create combined workers which size goes from 1
to the total number of CPU workers in the system. \ref STARPU_MIN_WORKERSIZE
and \ref STARPU_MAX_WORKERSIZE can be used to change this default.
</dd>

<dt>STARPU_MIN_WORKERSIZE</dt>
<dd>
\anchor STARPU_MIN_WORKERSIZE
\addindex __env__STARPU_MIN_WORKERSIZE
\ref STARPU_MIN_WORKERSIZE
permits to specify the minimum size of the combined workers (instead of the default 2)
</dd>

<dt>STARPU_MAX_WORKERSIZE</dt>
<dd>
\anchor STARPU_MAX_WORKERSIZE
\addindex __env__STARPU_MAX_WORKERSIZE
\ref STARPU_MAX_WORKERSIZE
permits to specify the minimum size of the combined workers (instead of the
number of CPU workers in the system)
</dd>

<dt>STARPU_SYNTHESIZE_ARITY_COMBINED_WORKER</dt>
<dd>
\anchor STARPU_SYNTHESIZE_ARITY_COMBINED_WORKER
\addindex __env__STARPU_SYNTHESIZE_ARITY_COMBINED_WORKER
Let the user decide how many elements are allowed between combined workers
created from hwloc information. For instance, in the case of sockets with 6
cores without shared L2 caches, if \ref STARPU_SYNTHESIZE_ARITY_COMBINED_WORKER is
set to 6, no combined worker will be synthesized beyond one for the socket
and one per core. If it is set to 3, 3 intermediate combined workers will be
synthesized, to divide the socket cores into 3 chunks of 2 cores. If it set to
2, 2 intermediate combined workers will be synthesized, to divide the the socket
cores into 2 chunks of 3 cores, and then 3 additional combined workers will be
synthesized, to divide the former synthesized workers into a bunch of 2 cores,
and the remaining core (for which no combined worker is synthesized since there
is already a normal worker for it).

The default, 2, thus makes StarPU tend to building a binary trees of combined
workers.
</dd>

<dt>STARPU_DISABLE_ASYNCHRONOUS_COPY</dt>
<dd>
\anchor STARPU_DISABLE_ASYNCHRONOUS_COPY
\addindex __env__STARPU_DISABLE_ASYNCHRONOUS_COPY
Disable asynchronous copies between CPU and GPU devices.
The AMD implementation of OpenCL is known to
fail when copying data asynchronously. When using this implementation,
it is therefore necessary to disable asynchronous data transfers.
</dd>

<dt>STARPU_DISABLE_ASYNCHRONOUS_CUDA_COPY</dt>
<dd>
\anchor STARPU_DISABLE_ASYNCHRONOUS_CUDA_COPY
\addindex __env__STARPU_DISABLE_ASYNCHRONOUS_CUDA_COPY
Disable asynchronous copies between CPU and CUDA devices.
</dd>

<dt>STARPU_DISABLE_ASYNCHRONOUS_OPENCL_COPY</dt>
<dd>
\anchor STARPU_DISABLE_ASYNCHRONOUS_OPENCL_COPY
\addindex __env__STARPU_DISABLE_ASYNCHRONOUS_OPENCL_COPY
Disable asynchronous copies between CPU and OpenCL devices.
The AMD implementation of OpenCL is known to
fail when copying data asynchronously. When using this implementation,
it is therefore necessary to disable asynchronous data transfers.
</dd>

<dt>STARPU_DISABLE_ASYNCHRONOUS_MIC_COPY</dt>
<dd>
\anchor STARPU_DISABLE_ASYNCHRONOUS_MIC_COPY
\addindex __env__STARPU_DISABLE_ASYNCHRONOUS_MIC_COPY
Disable asynchronous copies between CPU and MIC devices.
</dd>

<dt>STARPU_DISABLE_ASYNCHRONOUS_MPI_MS_COPY</dt>
<dd>
\anchor STARPU_DISABLE_ASYNCHRONOUS_MPI_MS_COPY
\addindex __env__STARPU_DISABLE_ASYNCHRONOUS_MPI_MS_COPY
Disable asynchronous copies between CPU and MPI Slave devices.
</dd>

<dt>STARPU_ENABLE_CUDA_GPU_GPU_DIRECT</dt>
<dd>
\anchor STARPU_ENABLE_CUDA_GPU_GPU_DIRECT
\addindex __env__STARPU_ENABLE_CUDA_GPU_GPU_DIRECT
Enable (1) or Disable (0) direct CUDA transfers from GPU to GPU, without copying
through RAM. The default is Enabled.
This permits to test the performance effect of GPU-Direct.
</dd>

<dt>STARPU_DISABLE_PINNING</dt>
<dd>
\anchor STARPU_DISABLE_PINNING
\addindex __env__STARPU_DISABLE_PINNING
Disable (1) or Enable (0) pinning host memory allocated through starpu_malloc, starpu_memory_pin
and friends.  The default is Enabled.
This permits to test the performance effect of memory pinning.
</dd>

<dt>STARPU_MIC_SINK_PROGRAM_NAME</dt>
<dd>
\anchor STARPU_MIC_SINK_PROGRAM_NAME
\addindex __env__STARPU_MIC_SINK_PROGRAM_NAME
todo
</dd>

<dt>STARPU_MIC_SINK_PROGRAM_PATH</dt>
<dd>
\anchor STARPU_MIC_SINK_PROGRAM_PATH
\addindex __env__STARPU_MIC_SINK_PROGRAM_PATH
todo
</dd>

<dt>STARPU_MIC_PROGRAM_PATH</dt>
<dd>
\anchor STARPU_MIC_PROGRAM_PATH
\addindex __env__STARPU_MIC_PROGRAM_PATH
todo
</dd>

</dl>

\section ConfiguringTheSchedulingEngine Configuring The Scheduling Engine

<dl>

<dt>STARPU_SCHED</dt>
<dd>
\anchor STARPU_SCHED
\addindex __env__STARPU_SCHED
Choose between the different scheduling policies proposed by StarPU: work
random, stealing, greedy, with performance models, etc.

Use <c>STARPU_SCHED=help</c> to get the list of available schedulers.
</dd>

<dt>STARPU_MIN_PRIO</dt>
<dd>
\anchor STARPU_MIN_PRIO_env
\addindex __env__STARPU_MIN_PRIO
Set the mininum priority used by priorities-aware schedulers.
</dd>

<dt>STARPU_MAX_PRIO</dt>
<dd>
\anchor STARPU_MAX_PRIO_env
\addindex __env__STARPU_MAX_PRIO
Set the maximum priority used by priorities-aware schedulers.
</dd>

<dt>STARPU_CALIBRATE</dt>
<dd>
\anchor STARPU_CALIBRATE
\addindex __env__STARPU_CALIBRATE
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 <c>dm</c> and <c>dmda</c> scheduling policies.
</dd>

<dt>STARPU_CALIBRATE_MINIMUM</dt>
<dd>
\anchor STARPU_CALIBRATE_MINIMUM
\addindex __env__STARPU_CALIBRATE_MINIMUM
This defines the minimum number of calibration measurements that will be made
before considering that the performance model is calibrated. The default value is 10.
</dd>

<dt>STARPU_BUS_CALIBRATE</dt>
<dd>
\anchor STARPU_BUS_CALIBRATE
\addindex __env__STARPU_BUS_CALIBRATE
If this variable is set to 1, the bus is recalibrated during intialization.
</dd>

<dt>STARPU_PREFETCH</dt>
<dd>
\anchor STARPU_PREFETCH
\addindex __env__STARPU_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.
</dd>

<dt>STARPU_SCHED_ALPHA</dt>
<dd>
\anchor STARPU_SCHED_ALPHA
\addindex __env__STARPU_SCHED_ALPHA
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.
</dd>

<dt>STARPU_SCHED_BETA</dt>
<dd>
\anchor STARPU_SCHED_BETA
\addindex __env__STARPU_SCHED_BETA
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.
</dd>

<dt>STARPU_SCHED_GAMMA</dt>
<dd>
\anchor STARPU_SCHED_GAMMA
\addindex __env__STARPU_SCHED_GAMMA
Define the execution time penalty of a joule (\ref Energy-basedScheduling).
</dd>

<dt>STARPU_IDLE_POWER</dt>
<dd>
\anchor STARPU_IDLE_POWER
\addindex __env__STARPU_IDLE_POWER
Define the idle power of the machine (\ref Energy-basedScheduling).
</dd>

<dt>STARPU_PROFILING</dt>
<dd>
\anchor STARPU_PROFILING
\addindex __env__STARPU_PROFILING
Enable on-line performance monitoring (\ref EnablingOn-linePerformanceMonitoring).
</dd>

</dl>

\section Extensions Extensions

<dl>

<dt>SOCL_OCL_LIB_OPENCL</dt>
<dd>
\anchor SOCL_OCL_LIB_OPENCL
\addindex __env__SOCL_OCL_LIB_OPENCL
THE SOCL test suite is only run when the environment variable
\ref SOCL_OCL_LIB_OPENCL is defined. It should contain the location
of the file <c>libOpenCL.so</c> of the OCL ICD implementation.
</dd>

<dt>OCL_ICD_VENDORS</dt>
<dd>
\anchor OCL_ICD_VENDORS
\addindex __env__OCL_ICD_VENDORS
When using SOCL with OpenCL ICD
(https://forge.imag.fr/projects/ocl-icd/), this variable may be used
to point to the directory where ICD files are installed. The default
directory is <c>/etc/OpenCL/vendors</c>. StarPU installs ICD
files in the directory <c>$prefix/share/starpu/opencl/vendors</c>.
</dd>

<dt>STARPU_COMM_STATS</dt>
<dd>
\anchor STARPU_COMM_STATS
\addindex __env__STARPU_COMM_STATS
Communication statistics for starpumpi (\ref MPISupport)
will be enabled when the environment variable \ref STARPU_COMM_STATS
is defined to an value other than 0.
</dd>

<dt>STARPU_MPI_CACHE</dt>
<dd>
\anchor STARPU_MPI_CACHE
\addindex __env__STARPU_MPI_CACHE
Communication cache for starpumpi (\ref MPISupport) will be
disabled when the environment variable \ref STARPU_MPI_CACHE is set
to 0. It is enabled by default or for any other values of the variable
\ref STARPU_MPI_CACHE.
</dd>

<dt>STARPU_MPI_COMM</dt>
<dd>
\anchor STARPU_MPI_COMM
\addindex __env__STARPU_MPI_COMM
Communication trace for starpumpi (\ref MPISupport) will be
enabled when the environment variable \ref STARPU_MPI_COMM is set
to 1, and StarPU has been configured with the option
\ref enable-verbose "--enable-verbose".
</dd>

<dt>STARPU_MPI_CACHE_STATS</dt>
<dd>
\anchor STARPU_MPI_CACHE_STATS
\addindex __env__STARPU_MPI_CACHE_STATS
When set to 1, statistics are enabled for the communication cache (\ref MPISupport). For now,
it prints messages on the standard output when data are added or removed from the received
communication cache.
</dd>

<dt>STARPU_MPI_PRIORITIES</dt>
<dd>
\anchor STARPU_MPI_PRIORITIES
\addindex __env__STARPU_MPI_PRIORITIES
When set to 0, the use of priorities to order MPI communications is disabled
(\ref MPISupport).
</dd>

<dt>STARPU_MPI_FAKE_SIZE</dt>
<dd>
\anchor STARPU_MPI_FAKE_SIZE
\addindex __env__STARPU_MPI_FAKE_SIZE
Setting to a number makes StarPU believe that there are as many MPI nodes, even
if it was run on only one MPI node. This allows e.g. to simulate the execution
of one of the nodes of a big cluster without actually running the rest.
It of course does not provide computation results and timing.
</dd>

<dt>STARPU_MPI_FAKE_RANK</dt>
<dd>
\anchor STARPU_MPI_FAKE_RANK
\addindex __env__STARPU_MPI_FAKE_RANK
Setting to a number makes StarPU believe that it runs the given MPI node, even
if it was run on only one MPI node. This allows e.g. to simulate the execution
of one of the nodes of a big cluster without actually running the rest.
It of course does not provide computation results and timing.
</dd>

<dt>STARPU_SIMGRID_CUDA_MALLOC_COST</dt>
<dd>
\anchor STARPU_SIMGRID_CUDA_MALLOC_COST
\addindex __env__STARPU_SIMGRID_CUDA_MALLOC_COST
When set to 1 (which is the default), CUDA malloc costs are taken into account
in simgrid mode.
</dd>

<dt>STARPU_SIMGRID_CUDA_QUEUE_COST</dt>
<dd>
\anchor STARPU_SIMGRID_CUDA_QUEUE_COST
\addindex __env__STARPU_SIMGRID_CUDA_QUEUE_COST
When set to 1 (which is the default), CUDA task and transfer queueing costs are
taken into account in simgrid mode.
</dd>

<dt>STARPU_PCI_FLAT</dt>
<dd>
\anchor STARPU_PCI_FLAT
\addindex __env__STARPU_PCI_FLAT
When unset or set to 0, the platform file created for simgrid will
contain PCI bandwidths and routes.
</dd>

<dt>STARPU_SIMGRID_QUEUE_MALLOC_COST</dt>
<dd>
\anchor STARPU_SIMGRID_QUEUE_MALLOC_COST
\addindex __env__STARPU_SIMGRID_QUEUE_MALLOC_COST
When unset or set to 1, simulate within simgrid the GPU transfer queueing.
</dd>

<dt>STARPU_MALLOC_SIMULATION_FOLD</dt>
<dd>
\anchor STARPU_MALLOC_SIMULATION_FOLD
\addindex __env__STARPU_MALLOC_SIMULATION_FOLD
This defines the size of the file used for folding virtual allocation, in
MiB. The default is 1, thus allowing 64GiB virtual memory when Linux's
<c>sysctl vm.max_map_count</c> value is the default 65535.
</dd>

<dt>STARPU_SIMGRID_TASK_SUBMIT_COST</dt>
<dd>
\anchor STARPU_SIMGRID_TASK_SUBMIT_COST
\addindex __env__STARPU_SIMGRID_TASK_SUBMIT_COST
When set to 1 (which is the default), task submission costs are taken into
account in simgrid mode. This provides more accurate simgrid predictions,
especially for the beginning of the execution.
</dd>

<dt>STARPU_SIMGRID_FETCHING_INPUT_COST</dt>
<dd>
\anchor STARPU_SIMGRID_FETCHING_INPUT_COST
\addindex __env__STARPU_SIMGRID_FETCHING_INPUT_COST
When set to 1 (which is the default), fetching input costs are taken into
account in simgrid mode. This provides more accurate simgrid predictions,
especially regarding data transfers.
</dd>

<dt>STARPU_SIMGRID_SCHED_COST</dt>
<dd>
\anchor STARPU_SIMGRID_SCHED_COST
\addindex __env__STARPU_SIMGRID_SCHED_COST
When set to 1 (0 is the default), scheduling costs are taken into
account in simgrid mode. This provides more accurate simgrid predictions,
and allows studying scheduling overhead of the runtime system. However,
it also makes simulation non-deterministic.
</dd>

</dl>

\section MiscellaneousAndDebug Miscellaneous And Debug

<dl>

<dt>STARPU_HOME</dt>
<dd>
\anchor STARPU_HOME
\addindex __env__STARPU_HOME
This specifies the main directory in which StarPU stores its
configuration files. The default is <c>$HOME</c> on Unix environments,
and <c>$USERPROFILE</c> on Windows environments.
</dd>

<dt>STARPU_PATH</dt>
<dd>
\anchor STARPU_PATH
\addindex __env__STARPU_PATH
Only used on  Windows environments.
This specifies the main directory in which StarPU is installed
(\ref RunningABasicStarPUApplicationOnMicrosoft)
</dd>

<dt>STARPU_PERF_MODEL_DIR</dt>
<dd>
\anchor STARPU_PERF_MODEL_DIR
\addindex __env__STARPU_PERF_MODEL_DIR
This specifies the main directory in which StarPU stores its
performance model files. The default is <c>$STARPU_HOME/.starpu/sampling</c>.
</dd>

<dt>STARPU_PERF_MODEL_HOMOGENEOUS_CPU</dt>
<dd>
\anchor STARPU_PERF_MODEL_HOMOGENEOUS_CPU
\addindex __env__STARPU_PERF_MODEL_HOMOGENEOUS_CPU
When this is set to 0, StarPU will assume that CPU devices do not have the same
performance, and thus use different performance models for them, thus making
kernel calibration much longer, since measurements have to be made for each CPU
core.
</dd>

<dt>STARPU_PERF_MODEL_HOMOGENEOUS_CUDA</dt>
<dd>
\anchor STARPU_PERF_MODEL_HOMOGENEOUS_CUDA
\addindex __env__STARPU_PERF_MODEL_HOMOGENEOUS_CUDA
When this is set to 1, StarPU will assume that all CUDA devices have the same
performance, and thus share performance models for them, thus allowing kernel
calibration to be much faster, since measurements only have to be once for all
CUDA GPUs.
</dd>

<dt>STARPU_PERF_MODEL_HOMOGENEOUS_OPENCL</dt>
<dd>
\anchor STARPU_PERF_MODEL_HOMOGENEOUS_OPENCL
\addindex __env__STARPU_PERF_MODEL_HOMOGENEOUS_OPENCL
When this is set to 1, StarPU will assume that all OPENCL devices have the same
performance, and thus share performance models for them, thus allowing kernel
calibration to be much faster, since measurements only have to be once for all
OPENCL GPUs.
</dd>

<dt>STARPU_PERF_MODEL_HOMOGENEOUS_MIC</dt>
<dd>
\anchor STARPU_PERF_MODEL_HOMOGENEOUS_MIC
\addindex __env__STARPU_PERF_MODEL_HOMOGENEOUS_MIC
When this is set to 1, StarPU will assume that all MIC devices have the same
performance, and thus share performance models for them, thus allowing kernel
calibration to be much faster, since measurements only have to be once for all
MIC GPUs.
</dd>

<dt>STARPU_PERF_MODEL_HOMOGENEOUS_MPI_MS</dt>
<dd>
\anchor STARPU_PERF_MODEL_HOMOGENEOUS_MPI_MS
\addindex __env__STARPU_PERF_MODEL_HOMOGENEOUS_MPI_MS
When this is set to 1, StarPU will assume that all MPI Slave devices have the same
performance, and thus share performance models for them, thus allowing kernel
calibration to be much faster, since measurements only have to be once for all
MPI Slaves.
</dd>

<dt>STARPU_PERF_MODEL_HOMOGENEOUS_SCC</dt>
<dd>
\anchor STARPU_PERF_MODEL_HOMOGENEOUS_SCC
\addindex __env__STARPU_PERF_MODEL_HOMOGENEOUS_SCC
When this is set to 1, StarPU will assume that all SCC devices have the same
performance, and thus share performance models for them, thus allowing kernel
calibration to be much faster, since measurements only have to be once for all
SCC GPUs.
</dd>

<dt>STARPU_HOSTNAME</dt>
<dd>
\anchor STARPU_HOSTNAME
\addindex __env__STARPU_HOSTNAME
When set, force the hostname to be used when dealing performance model
files. Models are indexed by machine name. When running for example on
a homogenenous cluster, it is possible to share the models between
machines by setting <c>export STARPU_HOSTNAME=some_global_name</c>.
</dd>

<dt>STARPU_OPENCL_PROGRAM_DIR</dt>
<dd>
\anchor STARPU_OPENCL_PROGRAM_DIR
\addindex __env__STARPU_OPENCL_PROGRAM_DIR
This specifies the directory where the OpenCL codelet source files are
located. The function starpu_opencl_load_program_source() looks
for the codelet in the current directory, in the directory specified
by the environment variable \ref STARPU_OPENCL_PROGRAM_DIR, in the
directory <c>share/starpu/opencl</c> of the installation directory of
StarPU, and finally in the source directory of StarPU.
</dd>

<dt>STARPU_SILENT</dt>
<dd>
\anchor STARPU_SILENT
\addindex __env__STARPU_SILENT
This variable allows to disable verbose mode at runtime when StarPU
has been configured with the option \ref enable-verbose "--enable-verbose". It also
disables the display of StarPU information and warning messages.
</dd>

<dt>STARPU_LOGFILENAME</dt>
<dd>
\anchor STARPU_LOGFILENAME
\addindex __env__STARPU_LOGFILENAME
This variable specifies in which file the debugging output should be saved to.
</dd>

<dt>STARPU_FXT_PREFIX</dt>
<dd>
\anchor STARPU_FXT_PREFIX
\addindex __env__STARPU_FXT_PREFIX
This variable specifies in which directory to save the trace generated if FxT is enabled. It needs to have a trailing '/' character.
</dd>

<dt>STARPU_FXT_TRACE</dt>
<dd>
\anchor STARPU_FXT_TRACE
\addindex __env__STARPU_FXT_TRACE
This variable specifies whether to generate (1) or not (0) the FxT trace in /tmp/prof_file_XXX_YYY . The default is 1 (generate it)
</dd>

<dt>STARPU_LIMIT_CUDA_devid_MEM</dt>
<dd>
\anchor STARPU_LIMIT_CUDA_devid_MEM
\addindex __env__STARPU_LIMIT_CUDA_devid_MEM
This variable specifies the maximum number of megabytes that should be
available to the application on the CUDA device with the identifier
<c>devid</c>. This variable is intended to be used for experimental
purposes as it emulates devices that have a limited amount of memory.
When defined, the variable overwrites the value of the variable
\ref STARPU_LIMIT_CUDA_MEM.
</dd>

<dt>STARPU_LIMIT_CUDA_MEM</dt>
<dd>
\anchor STARPU_LIMIT_CUDA_MEM
\addindex __env__STARPU_LIMIT_CUDA_MEM
This variable specifies the maximum number of megabytes that should be
available to the application on each CUDA devices. This variable is
intended to be used for experimental purposes as it emulates devices
that have a limited amount of memory.
</dd>

<dt>STARPU_LIMIT_OPENCL_devid_MEM</dt>
<dd>
\anchor STARPU_LIMIT_OPENCL_devid_MEM
\addindex __env__STARPU_LIMIT_OPENCL_devid_MEM
This variable specifies the maximum number of megabytes that should be
available to the application on the OpenCL device with the identifier
<c>devid</c>. This variable is intended to be used for experimental
purposes as it emulates devices that have a limited amount of memory.
When defined, the variable overwrites the value of the variable
\ref STARPU_LIMIT_OPENCL_MEM.
</dd>

<dt>STARPU_LIMIT_OPENCL_MEM</dt>
<dd>
\anchor STARPU_LIMIT_OPENCL_MEM
\addindex __env__STARPU_LIMIT_OPENCL_MEM
This variable specifies the maximum number of megabytes that should be
available to the application on each OpenCL devices. This variable is
intended to be used for experimental purposes as it emulates devices
that have a limited amount of memory.
</dd>

<dt>STARPU_LIMIT_CPU_MEM</dt>
<dd>
\anchor STARPU_LIMIT_CPU_MEM
\addindex __env__STARPU_LIMIT_CPU_MEM
This variable specifies the maximum number of megabytes that should be
available to the application in the main CPU memory. Setting it enables allocation
cache in main memory. Setting it to zero lets StarPU overflow memory.
</dd>

<dt>STARPU_LIMIT_CPU_NUMA_devid_MEM</dt>
<dd>
\anchor STARPU_LIMIT_CPU_NUMA_devid_MEM
\addindex __env__STARPU_LIMIT_CPU_NUMA_devid_MEM
This variable specifies the maximum number of megabytes that should be
available to the application on the NUMA node with the OS identifier <c>devid</c>.
</dd>

<dt>STARPU_MINIMUM_AVAILABLE_MEM</dt>
<dd>
\anchor STARPU_MINIMUM_AVAILABLE_MEM
\addindex __env__STARPU_MINIMUM_AVAILABLE_MEM
This specifies the minimum percentage of memory that should be available in GPUs
(or in main memory, when using out of core), below which a reclaiming pass is
performed. The default is 0%.
</dd>

<dt>STARPU_TARGET_AVAILABLE_MEM</dt>
<dd>
\anchor STARPU_TARGET_AVAILABLE_MEM
\addindex __env__STARPU_TARGET_AVAILABLE_MEM
This specifies the target percentage of memory that should be reached in
GPUs (or in main memory, when using out of core), when performing a periodic
reclaiming pass. The default is 0%.
</dd>

<dt>STARPU_MINIMUM_CLEAN_BUFFERS</dt>
<dd>
\anchor STARPU_MINIMUM_CLEAN_BUFFERS
\addindex __env__STARPU_MINIMUM_CLEAN_BUFFERS
This specifies the minimum percentage of number of buffers that should be clean in GPUs
(or in main memory, when using out of core), below which asynchronous writebacks will be
issued. The default is 5%.
</dd>

<dt>STARPU_TARGET_CLEAN_BUFFERS</dt>
<dd>
\anchor STARPU_TARGET_CLEAN_BUFFERS
\addindex __env__STARPU_TARGET_CLEAN_BUFFERS
This specifies the target percentage of number of buffers that should be reached in
GPUs (or in main memory, when using out of core), when performing an asynchronous
writeback pass. The default is 10%.
</dd>

<dt>STARPU_DIDUSE_BARRIER</dt>
<dd>
\anchor STARPU_DIDUSE_BARRIER
\addindex __env__STARPU_DIDUSE_BARRIER
When set to 1, StarPU will never evict a piece of data if it has not been used
by at least one task. This avoids odd behaviors under high memory pressure, but
can lead to deadlocks, so is to be considered experimental only.
</dd>

<dt>STARPU_DISK_SWAP</dt>
<dd>
\anchor STARPU_DISK_SWAP
\addindex __env__STARPU_DISK_SWAP
This specifies a path where StarPU can push data when the main memory is getting
full.
</dd>

<dt>STARPU_DISK_SWAP_BACKEND</dt>
<dd>
\anchor STARPU_DISK_SWAP_BACKEND
\addindex __env__STARPU_DISK_SWAP_BACKEND
This specifies then backend to be used by StarPU to push data when the main
memory is getting full. The default is unistd (i.e. using read/write functions),
other values are stdio (i.e. using fread/fwrite), unistd_o_direct (i.e. using
read/write with O_DIRECT), leveldb (i.e. using a leveldb database), and hdf5
(i.e. using HDF5 library).
</dd>

<dt>STARPU_DISK_SWAP_SIZE</dt>
<dd>
\anchor STARPU_DISK_SWAP_SIZE
\addindex __env__STARPU_DISK_SWAP_SIZE
This specifies then maximum size in MiB to be used by StarPU to push data when the main
memory is getting full. The default is unlimited.
</dd>

<dt>STARPU_LIMIT_MAX_SUBMITTED_TASKS</dt>
<dd>
\anchor STARPU_LIMIT_MAX_SUBMITTED_TASKS
\addindex __env__STARPU_LIMIT_MAX_SUBMITTED_TASKS
This variable allows the user to control the task submission flow by specifying
to StarPU a maximum number of submitted tasks allowed at a given time, i.e. when
this limit is reached task submission becomes blocking until enough tasks have
completed, specified by \ref STARPU_LIMIT_MIN_SUBMITTED_TASKS.
Setting it enables allocation cache buffer reuse in main memory.
</dd>

<dt>STARPU_LIMIT_MIN_SUBMITTED_TASKS</dt>
<dd>
\anchor STARPU_LIMIT_MIN_SUBMITTED_TASKS
\addindex __env__STARPU_LIMIT_MIN_SUBMITTED_TASKS
This variable allows the user to control the task submission flow by specifying
to StarPU a submitted task threshold to wait before unblocking task submission. This
variable has to be used in conjunction with \ref STARPU_LIMIT_MAX_SUBMITTED_TASKS
which puts the task submission thread to
sleep.  Setting it enables allocation cache buffer reuse in main memory.
</dd>

<dt>STARPU_TRACE_BUFFER_SIZE</dt>
<dd>
\anchor STARPU_TRACE_BUFFER_SIZE
\addindex __env__STARPU_TRACE_BUFFER_SIZE
This sets the buffer size for recording trace events in MiB. Setting it to a big
size allows to avoid pauses in the trace while it is recorded on the disk. This
however also consumes memory, of course. The default value is 64.
</dd>

<dt>STARPU_GENERATE_TRACE</dt>
<dd>
\anchor STARPU_GENERATE_TRACE
\addindex __env__STARPU_GENERATE_TRACE
When set to <c>1</c>, this variable indicates that StarPU should automatically
generate a Paje trace when starpu_shutdown() is called.
</dd>

<dt>STARPU_GENERATE_TRACE_OPTIONS</dt>
<dd>
\anchor STARPU_GENERATE_TRACE_OPTIONS
\addindex __env__STARPU_GENERATE_TRACE_OPTIONS
When the variable \ref STARPU_GENERATE_TRACE is set to <c>1</c> to
generate a Paje trace, this variable can be set to specify options (see
<c>starpu_fxt_tool --help</c>).
</dd>

<dt>STARPU_ENABLE_STATS</dt>
<dd>
\anchor STARPU_ENABLE_STATS
\addindex __env__STARPU_ENABLE_STATS
When defined, enable gathering various data statistics (\ref DataStatistics).
</dd>

<dt>STARPU_MEMORY_STATS</dt>
<dd>
\anchor STARPU_MEMORY_STATS
\addindex __env__STARPU_MEMORY_STATS
When set to 0, disable the display of memory statistics on data which
have not been unregistered at the end of the execution (\ref MemoryFeedback).
</dd>

<dt>STARPU_MAX_MEMORY_USE</dt>
<dd>
\anchor STARPU_MAX_MEMORY_USE
\addindex __env__STARPU_MAX_MEMORY_USE
When set to 1, display at the end of the execution the maximum memory used by
StarPU for internal data structures during execution.
</dd>

<dt>STARPU_BUS_STATS</dt>
<dd>
\anchor STARPU_BUS_STATS
\addindex __env__STARPU_BUS_STATS
When defined, statistics about data transfers will be displayed when calling
starpu_shutdown() (\ref Profiling).
</dd>

<dt>STARPU_WORKER_STATS</dt>
<dd>
\anchor STARPU_WORKER_STATS
\addindex __env__STARPU_WORKER_STATS
When defined, statistics about the workers will be displayed when calling
starpu_shutdown() (\ref Profiling). When combined with the
environment variable \ref STARPU_PROFILING, it displays the energy
consumption (\ref Energy-basedScheduling).
</dd>

<dt>STARPU_STATS</dt>
<dd>
\anchor STARPU_STATS
\addindex __env__STARPU_STATS
When set to 0, data statistics will not be displayed at the
end of the execution of an application (\ref DataStatistics).
</dd>

<dt>STARPU_WATCHDOG_TIMEOUT</dt>
<dd>
\anchor STARPU_WATCHDOG_TIMEOUT
\addindex __env__STARPU_WATCHDOG_TIMEOUT
When set to a value other than 0, allows to make StarPU print an error
message whenever StarPU does not terminate any task for the given time (in µs),
but lets the application continue normally. Should
be used in combination with \ref STARPU_WATCHDOG_CRASH
(see \ref DetectionStuckConditions).
</dd>

<dt>STARPU_WATCHDOG_CRASH</dt>
<dd>
\anchor STARPU_WATCHDOG_CRASH
\addindex __env__STARPU_WATCHDOG_CRASH
When set to a value other than 0, it triggers a crash when the watch
dog is reached, thus allowing to catch the situation in gdb, etc
(see \ref DetectionStuckConditions)
</dd>

<dt>STARPU_WATCHDOG_DELAY</dt>
<dd>
\anchor STARPU_WATCHDOG_DELAY
\addindex __env__STARPU_WATCHDOG_DELAY
This delays the activation of the watchdog by the given time (in µs). This can
be convenient for letting the application initialize data etc. before starting
to look for idle time.
</dd>

<dt>STARPU_TASK_BREAK_ON_PUSH</dt>
<dd>
\anchor STARPU_TASK_BREAK_ON_PUSH
\addindex __env__STARPU_TASK_BREAK_ON_PUSH
When this variable contains a job id, StarPU will raise SIGTRAP when the task
with that job id is being pushed to the scheduler, which will be nicely catched by debuggers
(see \ref DebuggingScheduling)
</dd>

<dt>STARPU_TASK_BREAK_ON_SCHED</dt>
<dd>
\anchor STARPU_TASK_BREAK_ON_SCHED
\addindex __env__STARPU_TASK_BREAK_ON_SCHED
When this variable contains a job id, StarPU will raise SIGTRAP when the task
with that job id is being scheduled by the scheduler (at a scheduler-specific
point), which will be nicely catched by debuggers.
This only works for schedulers which have such a scheduling point defined
(see \ref DebuggingScheduling)
</dd>

<dt>STARPU_TASK_BREAK_ON_POP</dt>
<dd>
\anchor STARPU_TASK_BREAK_ON_POP
\addindex __env__STARPU_TASK_BREAK_ON_POP
When this variable contains a job id, StarPU will raise SIGTRAP when the task
with that job id is being popped from the scheduler, which will be nicely catched by debuggers
(see \ref DebuggingScheduling)
</dd>

<dt>STARPU_TASK_BREAK_ON_EXEC</dt>
<dd>
\anchor STARPU_TASK_BREAK_ON_EXEC
\addindex __env__STARPU_TASK_BREAK_ON_EXEC
When this variable contains a job id, StarPU will raise SIGTRAP when the task
with that job id is being executed, which will be nicely catched by debuggers
(see \ref DebuggingScheduling)
</dd>

<dt>STARPU_DISABLE_KERNELS</dt>
<dd>
\anchor STARPU_DISABLE_KERNELS
\addindex __env__STARPU_DISABLE_KERNELS
When set to a value other than 1, it disables actually calling the kernel
functions, thus allowing to quickly check that the task scheme is working
properly, without performing the actual application-provided computation.
</dd>

<dt>STARPU_HISTORY_MAX_ERROR</dt>
<dd>
\anchor STARPU_HISTORY_MAX_ERROR
\addindex __env__STARPU_HISTORY_MAX_ERROR
History-based performance models will drop measurements which are really far
froom the measured average. This specifies the allowed variation. The default is
50 (%), i.e. the measurement is allowed to be x1.5 faster or /1.5 slower than the
average.
</dd>

<dt>STARPU_RAND_SEED</dt>
<dd>
\anchor STARPU_RAND_SEED
\addindex __env__STARPU_RAND_SEED
The random scheduler and some examples use random numbers for their own
working. Depending on the examples, the seed is by default juste always 0 or
the current time() (unless simgrid mode is enabled, in which case it is always
0). \ref STARPU_RAND_SEED allows to set the seed to a specific value.
</dd>

<dt>STARPU_IDLE_TIME</dt>
<dd>
\anchor STARPU_IDLE_TIME
\addindex __env__STARPU_IDLE_TIME
When set to a value being a valid filename, a corresponding file
will be created when shutting down StarPU. The file will contain the
sum of all the workers' idle time.
</dd>

<dt>STARPU_GLOBAL_ARBITER</dt>
<dd>
\anchor STARPU_GLOBAL_ARBITER
\addindex __env__STARPU_GLOBAL_ARBITER
When set to a positive value, StarPU will create a arbiter, which
implements an advanced but centralized management of concurrent data
accesses (see \ref ConcurrentDataAccess).
</dd>

<dt>STARPU_USE_NUMA</dt>
<dd>
\anchor STARPU_USE_NUMA
\addindex __env__STARPU_USE_NUMA
When defined, NUMA nodes are taking into account by StarPU. Otherwise, memory
is considered as only one node. This is experimental for now.

When enabled, STARPU_MAIN_MEMORY is a pointer to the NUMA node associated to the
first CPU worker if it exists, the NUMA node associated to the first GPU discovered otherwise.
If StarPU doesn't find any NUMA node after these step, STARPU_MAIN_MEMORY is the first NUMA node
discovered by StarPU.
</dd>

<dt>STARPU_IDLE_FILE</dt>
<dd>
\anchor STARPU_IDLE_FILE
\addindex __env__STARPU_IDLE_FILE
If the environment variable STARPU_IDLE_FILE is defined, a file named after its contents will be created at the end of the execution.
The file will contain the sum of the idle times of all the workers.
</dd>

</dl>

\section ConfiguringTheHypervisor Configuring The Hypervisor

<dl>

<dt>SC_HYPERVISOR_POLICY</dt>
<dd>
\anchor SC_HYPERVISOR_POLICY
\addindex __env__SC_HYPERVISOR_POLICY
Choose between the different resizing policies proposed by StarPU for the hypervisor:
idle, app_driven, feft_lp, teft_lp; ispeed_lp, throughput_lp etc.

Use <c>SC_HYPERVISOR_POLICY=help</c> to get the list of available policies for the hypervisor
</dd>

<dt>SC_HYPERVISOR_TRIGGER_RESIZE</dt>
<dd>
\anchor SC_HYPERVISOR_TRIGGER_RESIZE
\addindex __env__SC_HYPERVISOR_TRIGGER_RESIZE
Choose how should the hypervisor be triggered: <c>speed</c> if the resizing algorithm should
be called whenever the speed of the context does not correspond to an optimal precomputed value,
<c>idle</c> it the resizing algorithm should be called whenever the workers are idle for a period
longer than the value indicated when configuring the hypervisor.
</dd>

<dt>SC_HYPERVISOR_START_RESIZE</dt>
<dd>
\anchor SC_HYPERVISOR_START_RESIZE
\addindex __env__SC_HYPERVISOR_START_RESIZE
Indicate the moment when the resizing should be available. The value correspond to the percentage
of the total time of execution of the application. The default value is the resizing frame.
</dd>

<dt>SC_HYPERVISOR_MAX_SPEED_GAP</dt>
<dd>
\anchor SC_HYPERVISOR_MAX_SPEED_GAP
\addindex __env__SC_HYPERVISOR_MAX_SPEED_GAP
Indicate the ratio of speed difference between contexts that should trigger the hypervisor.
This situation may occur only when a theoretical speed could not be computed and the hypervisor
has no value to compare the speed to. Otherwise the resizing of a context is not influenced by the
the speed of the other contexts, but only by the the value that a context should have.
</dd>

<dt>SC_HYPERVISOR_STOP_PRINT</dt>
<dd>
\anchor SC_HYPERVISOR_STOP_PRINT
\addindex __env__SC_HYPERVISOR_STOP_PRINT
By default the values of the speed of the workers is printed during the execution
of the application. If the value 1 is given to this environment variable this printing
is not done.
</dd>

<dt>SC_HYPERVISOR_LAZY_RESIZE</dt>
<dd>
\anchor SC_HYPERVISOR_LAZY_RESIZE
\addindex __env__SC_HYPERVISOR_LAZY_RESIZE
By default the hypervisor resizes the contexts in a lazy way, that is workers are firstly added to a new context
before removing them from the previous one. Once this workers are clearly taken into account
into the new context (a task was poped there) we remove them from the previous one. However if the application
would like that the change in the distribution of workers should change right away this variable should be set to 0
</dd>

<dt>SC_HYPERVISOR_SAMPLE_CRITERIA</dt>
<dd>
\anchor SC_HYPERVISOR_SAMPLE_CRITERIA
\addindex __env__SC_HYPERVISOR_SAMPLE_CRITERIA
By default the hypervisor uses a sample of flops when computing the speed of the contexts and of the workers.
If this variable is set to <c>time</c> the hypervisor uses a sample of time (10% of an aproximation of the total
execution time of the application)
</dd>

</dl>

*/