Configurable app plan functions
Possible tags:
<name> Name of the plan class, string without spaces, exact match
<type> type of the plan class, currently understood are 0 = CPU and 1 = CUDA
2 = ATI is suggested, but not supported in current code.
May be specified numerically (0, 1, 2) or as token (CPU, CUDA, ATI)
3 = NVidia OpenCL, 4 = ATI OpenCL.
<min_cuda_compcap> CUDA only: minimum compute capability
<max_cuda_compcap> CUDA only: maximum compute capability, set to 9999 to exclude emulation device
<min_cuda_version> CUDA only: minimum CUDA version
<max_cuda_version> CUDA only: maximum CUDA version
<min_opencl_version> OpenCL only: minimum required device version
IMPORTANT NOTE: the NVidia display driver version is only reported by Windows
core clients. Mac and Linux clients only report the CUDA version. The display
driver version will allways be 0 (zero) for these clients, hence this should
NEVER be used to restrict a plan class for platforms other than Windows!
NOTE#2: Reporting driver version has been added to recent Mac Clients (6.13.x)
NOTE#3: the driver_version may be specified negative. In this case its _absolute_
value is compared to the client's driver version, but only if this is reported.
If the Client doesn't report a driver version, this check is skipped.
<min_driver_version> GPU only: minimum display driver version
<max_driver_version> GPU only: minimum display driver version
<min_gpu_ram_mb> GPU only: minimum required amount of video RAM (in MB)
<gpu_ram_used_mb> GPU only: video RAM a task will actually use (in MB)
<project_prefs_tag> name of a tag from the project specific preferences that can be used to enable
or disable this plan-class (scanned as double, 0.0 if not present)
<project_prefs_min> min value this tag can have to allow this plan-class
<project_prefs_max> max value this tag can have to allow this plan-class
<gpu_utilization_tag> name of a tag from the project specific preferences which values is a custom
gpu utilization factor supplied by the user. The 'ngpus' setting of the plan class
will be multiplied by this when present.
<cpu_feature> CPU features required for this plan class. Multiple tags allowed. All features
lowercase (e.g. sse2, altivec). Both host.p_features and host.p_model are checked
<min_macos_version> Deprecated: min Darwin version required for this plan class, 0 = no check,
numeric: 1000 * major version + 100 * minor version + patchlevel
<max_macos_version> Deprecated: max Darwin version allowed for this plan class, 0 = no limit
<os_version> regexp specifying an OS version (should work for all OS that way)
<speedup> speedup over standard "sequential" App for this platform
<peak_flops_factor> correct the (theoretical) peak flops by that factor (assumed efficency)
<avg_ncpus>
<max_ncpus>
<ngpus> GPU only: number / fraction of GPUs used, defaults 0 for CPU plan classes, 1 otherwise
if ngpus < 0, set ncudas by the fraction of the total video RAM a tasks would take
<gpu_flops>
<cpu_flops> GPU only: if both gpu_flops and cpu_flops are set, compuute
hu.avg_ncpus = avg_ncpus * sreq.host.p_fpops / cpu_flops and
projected_flops = cp.peak_flops / gpu_flops * speedup + 1.0 / hu.avg_ncpus;
Here is an example of three plan class specifications, two CPU, one CUDA.
<plan_classes>
<plan_class>
<name> CUDA32 </name>
<min_cuda_compcap> 100 </min_cuda_compcap>
<max_cuda_compcap> 9999 </max_cuda_compcap>
<min_cuda_version> 3020 </min_cuda_version>
<min_driver_version> 26000 </min_driver_version>
<max_driver_version> 99999 </max_driver_version>
<min_gpu_ram_mb> 300 </min_gpu_ram_mb>
<gpu_ram_used_mb> 300 </gpu_ram_used_mb>
<speedup> 10.0 </speedup>
<avgncpus> 0.2 </avgncpus>
</plan_class>
<plan_class>
<name> BRP3SSE </name>
<cpu_feature> sse </cpu_feature>
<project_prefs_tag> also_run_cpu </project_prefs_tag>
<project_prefs_max> 0 </project_prefs_max>
</plan_class>
<plan_class>
<name> ALTIVEC </name>
<cpu_feature> altivec </cpu_feature>
<min_macos_version> 80000 </min_macos_version>
<speedup> 1.4 </speedup>
</plan_class>
</plan_classes>