Home
last modified time | relevance | path

Searched refs:GPU (Results 76 – 100 of 7702) sorted by relevance

12345678910>>...309

/dports/science/gromacs/gromacs-2021.4/docs/user-guide/
H A Dmdrun-performance.rst98 GPU
569 specify both GPU availability and GPU task assignment.
575 "0011" specifies that the first two GPU tasks will use GPU 0,
610 Mapping of GPU IDs to the 4 GPU tasks in the 4 ranks on this node:
614 on GPU 0, and 1 rank to compute PME on GPU 1.
957 * Wait GPU nonlocal
958 * Wait GPU local
959 * Wait PME GPU spread
960 * Wait PME GPU gather
961 * Reduce PME GPU Force
[all …]
/dports/www/chromium-legacy/chromium-88.0.4324.182/third_party/perfetto/docs/data-sources/
H A Dgpu.md1 # GPU chapter
5 ## GPU Frequency
7 GPU frequency can be included in the trace by adding the ftrace category.
20 ## GPU Counters
22 GPU counters can be configured by adding the data source to the trace config as follows:
/dports/www/chromium-legacy/chromium-88.0.4324.182/docs/gpu/
H A Dpixel_wrangling.md1 # GPU Bots & Pixel Wrangling
7 GPU Pixel Wrangling is the process of keeping various GPU bots green. On the
26 ## GPU Bots' Waterfalls
34 * [Chromium GPU]
36 * [Chromium GPU FYI]
120 GPU bots.
141 [GPU Bots' Waterfalls](#GPU-Bots_Waterfalls) under the
142 [Chromium GPU][Sheriff-O-Matic] tab!
183 1. Make sure the GPU try servers are in good health.
303 on ssh'ing in to the GPU bots.
[all …]
/dports/lang/pocl/pocl-1.8/examples/ViennaCL/
H A Dmatrix_col_double-test-opencl.stdout73 Division with GPU scalar: PASSED!
234 Division with GPU scalar: PASSED!
395 Division with GPU scalar: PASSED!
556 Division with GPU scalar: PASSED!
717 Division with GPU scalar: PASSED!
878 Division with GPU scalar: PASSED!
1039 Division with GPU scalar: PASSED!
1200 Division with GPU scalar: PASSED!
1361 Division with GPU scalar: PASSED!
1522 Division with GPU scalar: PASSED!
[all …]
H A Dmatrix_col_float-test-opencl.stdout74 Division with GPU scalar: PASSED!
235 Division with GPU scalar: PASSED!
396 Division with GPU scalar: PASSED!
557 Division with GPU scalar: PASSED!
718 Division with GPU scalar: PASSED!
879 Division with GPU scalar: PASSED!
1040 Division with GPU scalar: PASSED!
1201 Division with GPU scalar: PASSED!
1362 Division with GPU scalar: PASSED!
1523 Division with GPU scalar: PASSED!
[all …]
H A Dmatrix_row_double-test-opencl.stdout73 Division with GPU scalar: PASSED!
234 Division with GPU scalar: PASSED!
395 Division with GPU scalar: PASSED!
556 Division with GPU scalar: PASSED!
717 Division with GPU scalar: PASSED!
878 Division with GPU scalar: PASSED!
1039 Division with GPU scalar: PASSED!
1200 Division with GPU scalar: PASSED!
1361 Division with GPU scalar: PASSED!
1522 Division with GPU scalar: PASSED!
[all …]
H A Dmatrix_row_float-test-opencl.stdout74 Division with GPU scalar: PASSED!
235 Division with GPU scalar: PASSED!
396 Division with GPU scalar: PASSED!
557 Division with GPU scalar: PASSED!
718 Division with GPU scalar: PASSED!
879 Division with GPU scalar: PASSED!
1040 Division with GPU scalar: PASSED!
1201 Division with GPU scalar: PASSED!
1362 Division with GPU scalar: PASSED!
1523 Division with GPU scalar: PASSED!
[all …]
H A Dmatrix_vector-test-opencl.stdout19 Scaled rank 1 update - GPU Scalar
32 Scaled rank 1 update - GPU Scalar
45 Scaled rank 1 update - GPU Scalar
58 Scaled rank 1 update - GPU Scalar
71 Scaled rank 1 update - GPU Scalar
84 Scaled rank 1 update - GPU Scalar
97 Scaled rank 1 update - GPU Scalar
110 Scaled rank 1 update - GPU Scalar
123 Scaled rank 1 update - GPU Scalar
136 Scaled rank 1 update - GPU Scalar
[all …]
/dports/www/qt5-webengine/qtwebengine-everywhere-src-5.15.2/src/3rdparty/chromium/docs/gpu/
H A Dpixel_wrangling.md1 # GPU Bots & Pixel Wrangling
7 GPU Pixel Wrangling is the process of keeping various GPU bots green. On the
17 * [Chrome GPU Fleet Status](http://vi/chrome-infra/Projects/gpu)
26 ## GPU Bots' Waterfalls
34 * [Chromium GPU]
36 * [Chromium GPU FYI]
111 GPU bots.
168 1. Make sure the GPU try servers are in good health.
246 (NVIDIA/AMD/Intel), and a specific GPU device.
288 on ssh'ing in to the GPU bots.
[all …]
/dports/graphics/opencv/opencv-4.5.3/modules/core/doc/
H A Dcuda.markdown21 performance. It is helpful to understand the cost of various operations, what the GPU does, what the
30 code, except for cuda::getCudaEnabledDeviceCount(). The latter function returns zero GPU count in
33 function, you can implement a high-level algorithm that will detect GPU presence at runtime and
34 choose an appropriate implementation (CPU or GPU) accordingly.
40 Binary code often implies a specific GPU architecture and generation, so the compatibility with
45 At the first call, the PTX code is compiled to binary code for the particular GPU using a JIT
60 On a GPU with CC 1.0, you can still compile the CUDA module and most of the functions will run
64 You can always determine at runtime whether the OpenCV GPU-built binaries (or PTX code) are
65 compatible with your GPU. The function cuda::DeviceInfo::isCompatible returns the compatibility
81 2. Process each pair of stripes (from the left and right images) on a separate Fermi\* GPU.
[all …]
/dports/misc/mxnet/incubator-mxnet-1.9.0/julia/test/unittest/
H A Dcontext.jl37 @context mx.GPU 24 begin
39 @test ctx.device_type == mx.GPU
50 @test ctx.device_type == mx.GPU
54 @context mx.GPU 123 begin
58 @context mx.GPU begin
60 @test ctx.device_type == mx.GPU
74 @test ctx.device_type == mx.GPU
80 @test ctx.device_type == mx.GPU
/dports/misc/py-mxnet/incubator-mxnet-1.9.0/julia/test/unittest/
H A Dcontext.jl37 @context mx.GPU 24 begin
39 @test ctx.device_type == mx.GPU
50 @test ctx.device_type == mx.GPU
54 @context mx.GPU 123 begin
58 @context mx.GPU begin
60 @test ctx.device_type == mx.GPU
74 @test ctx.device_type == mx.GPU
80 @test ctx.device_type == mx.GPU
/dports/devel/taskflow/taskflow-3.2.0/doxygen/cookbook/
H A Dgpu_tasking_cudaflow_capturer.dox3 /** @page GPUTaskingcudaFlowCapturer GPU Tasking (%cudaFlowCapturer)
6 to capture information on GPU activities that are submitted to the stream
60 GPU parallelism.
107 You can emplace a %cudaFlowCapturer on a specific GPU.
111 // here, capturer is under GPU device 2
116 The above example creates a capturer on GPU 2.
117 When the executor runs the callable, it switches to GPU 2
122 GPU context as the capturer.
233 tf::Taskflow and offloads it to a GPU from the caller thread.
253 to decide its GPU context.
[all …]
/dports/www/chromium-legacy/chromium-88.0.4324.182/third_party/blink/renderer/modules/webgpu/
H A Dnavigator_gpu.h15 class GPU; variable
26 static GPU* gpu(ScriptState* script_state, Navigator&);
27 GPU* gpu(ScriptState* script_state);
34 Member<GPU> gpu_;
H A Dworker_navigator_gpu.h14 class GPU; variable
26 static GPU* gpu(ScriptState* script_state, WorkerNavigator&);
27 GPU* gpu(ScriptState* script_state);
34 Member<GPU> gpu_;
/dports/www/qt5-webengine/qtwebengine-everywhere-src-5.15.2/src/3rdparty/chromium/third_party/blink/renderer/modules/webgpu/
H A Dnavigator_gpu.h15 class GPU; variable
28 static GPU* gpu(ScriptState* script_state, Navigator&);
29 GPU* gpu(ScriptState* script_state);
36 Member<GPU> gpu_;
H A Dworker_navigator_gpu.h14 class GPU; variable
28 static GPU* gpu(ScriptState* script_state, WorkerNavigator&);
29 GPU* gpu(ScriptState* script_state);
36 Member<GPU> gpu_;
/dports/net/mpich/mpich-3.4.3/modules/ucx/docs/source/
H A Dfaq.md85 * **AMD GPU support** - requires ROCm drivers
153 > * Applications using GPU memory must also specify GPU transports for detecting and
250 ## Working with GPU
252 ### GPU support argument
254 #### How UCX supports GPU?
258 be either host or GPU memory.
266 #### Which UCX APIs support GPU memory?
271 #### How to run UCX with GPU support?
274 GPU memory (for example,
277 example, with MPI) and whenever GPU memory is passed to UCX, it either use GPU-direct
[all …]
/dports/devel/py-distributed/distributed-2021.11.2/docs/source/
H A Dresources.rst8 GPUs each. We may have a thousand tasks, a hundred of which require a GPU and
11 GPU-constrained tasks to GPU-enabled workers. Additionally we need to be sure
12 to constrain the number of GPU tasks that run concurrently on any given worker
19 resources in any particular way (Dask does not know what a GPU is) and it is up
35 dask-worker scheduler:8786 --resources "GPU=2"
36 dask-worker scheduler:8786 --resources "GPU=2"
54 with dask.annotate(resources={'GPU': 1}):
71 dask-worker scheduler:8786 --resources "GPU=2"
84 with dask.config.set({"distributed.worker.resources.GPU": 2}):
111 dask-worker scheduler:8786 --nprocs 2 --resources "GPU=1"
[all …]
/dports/devel/gitlab-runner/gitlab-runner-8925d9a06fd8e452e2161a768462652a2a13111f/docs/configuration/
H A Dgpus.md36 [the node selector chooses a node with GPU support](https://kubernetes.io/docs/tasks/manage-gpus/sc…
39 with [GPU-enabled instances](https://docs.aws.amazon.com/dlami/latest/devguide/gpu.html).
44 way to ensure that a GPU is enabled for a CI job is to run `nvidia-smi`
60 | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
61 | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
71 | GPU GI CI PID Type Process name GPU Memory |
78 If the hardware does not support a GPU, `nvidia-smi` should fail either because
/dports/www/qt5-webengine/qtwebengine-everywhere-src-5.15.2/src/3rdparty/chromium/infra/config/consoles/
H A Dchromium.gpu.fyi.star7 builder = 'ci/GPU FYI Win Builder',
12 builder = 'ci/GPU FYI Win x64 Builder',
17 builder = 'ci/GPU FYI Win dEQP Builder',
22 builder = 'ci/GPU FYI Win x64 dEQP Builder',
37 builder = 'ci/GPU FYI Win Builder (dbg)',
47 builder = 'ci/GPU FYI XR Win x64 Builder',
162 builder = 'ci/GPU FYI Mac Builder',
167 builder = 'ci/GPU FYI Mac Builder (dbg)',
172 builder = 'ci/GPU FYI Mac dEQP Builder',
237 builder = 'ci/Mac FYI GPU ASAN Release',
[all …]
/dports/math/suitesparse-ldl/SuiteSparse-5.10.1/SPQR/Demo/
H A Dgo5.m1 % compares SPQR with SPQR+GPU on lots of sparse matrices
52 % 3: spqr on GPU with colamd
53 % 4: spqr on GPU with metis
102 % run SPQR without the GPU
156 fprintf ('skipping rank deficient case for the GPU\n') ;
161 % run SPQR with the GPU
189 % % GPU version failed
226 fprintf ('GPU colamd factime %8.2f gflops : %8.2f\n', ...
229 fprintf ('GPU metis factime %8.2f gflops : %8.2f\n', ...
238 title ('GPU speedup (colamd)') ;
[all …]
/dports/math/suitesparse-config/SuiteSparse-5.10.1/SPQR/Demo/
H A Dgo5.m1 % compares SPQR with SPQR+GPU on lots of sparse matrices
52 % 3: spqr on GPU with colamd
53 % 4: spqr on GPU with metis
102 % run SPQR without the GPU
156 fprintf ('skipping rank deficient case for the GPU\n') ;
161 % run SPQR with the GPU
189 % % GPU version failed
226 fprintf ('GPU colamd factime %8.2f gflops : %8.2f\n', ...
229 fprintf ('GPU metis factime %8.2f gflops : %8.2f\n', ...
238 title ('GPU speedup (colamd)') ;
[all …]
/dports/math/suitesparse-graphblas/SuiteSparse-5.10.1/SPQR/Demo/
H A Dgo5.m1 % compares SPQR with SPQR+GPU on lots of sparse matrices
52 % 3: spqr on GPU with colamd
53 % 4: spqr on GPU with metis
102 % run SPQR without the GPU
156 fprintf ('skipping rank deficient case for the GPU\n') ;
161 % run SPQR with the GPU
189 % % GPU version failed
226 fprintf ('GPU colamd factime %8.2f gflops : %8.2f\n', ...
229 fprintf ('GPU metis factime %8.2f gflops : %8.2f\n', ...
238 title ('GPU speedup (colamd)') ;
[all …]
/dports/math/suitesparse-amd/SuiteSparse-5.10.1/SPQR/Demo/
H A Dgo5.m1 % compares SPQR with SPQR+GPU on lots of sparse matrices
52 % 3: spqr on GPU with colamd
53 % 4: spqr on GPU with metis
102 % run SPQR without the GPU
156 fprintf ('skipping rank deficient case for the GPU\n') ;
161 % run SPQR with the GPU
189 % % GPU version failed
226 fprintf ('GPU colamd factime %8.2f gflops : %8.2f\n', ...
229 fprintf ('GPU metis factime %8.2f gflops : %8.2f\n', ...
238 title ('GPU speedup (colamd)') ;
[all …]

12345678910>>...309