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/external/tensorflow/tensorflow/tools/ci_build/
DDockerfile.rbe.cuda9.0-cudnn7-ubuntu14.0416 …apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1404/x86_6…
19 …echo "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64 /" > /etc/apt…
20 …b https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64 /" > /etc…
24 ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:${PATH}
37 ENV LD_LIBRARY_PATH /usr/local/nvidia/lib:/usr/local/nvidia/lib64:/usr/local/cuda/lib64/stubs
39 LABEL com.nvidia.volumes.needed="nvidia_driver"
40 LABEL com.nvidia.cuda.version="${CUDA_VERSION}"
41 LABEL com.nvidia.cudnn.version="${CUDNN_VERSION}"
63 RUN echo "/usr/local/nvidia/lib" >> /etc/ld.so.conf.d/nvidia.conf && \
64 echo "/usr/local/nvidia/lib64" >> /etc/ld.so.conf.d/nvidia.conf
[all …]
DDockerfile.rbe.cuda10.0-cudnn7-ubuntu14.0413 …apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_6…
16 …echo "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64 /" > /etc/apt…
17 …b https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64 /" > /etc…
36 LABEL com.nvidia.cudnn.version="${CUDNN_VERSION}"
59 # https://github.com/NVIDIA/nvidia-docker/issues/775
DDockerfile.rbe.cuda11.0-cudnn8-ubuntu18.04-manylinux2010-multipython11 FROM nvidia/cuda:11.0-cudnn8-devel-ubuntu18.04 as devtoolset
38 FROM nvidia/cuda:11.0-cudnn8-devel-ubuntu18.04
44 deb https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64 / \
45 > /etc/apt/sources.list.d/nvidia-ml.list \
DDockerfile.custom_op_ubuntu_16_cuda10.03 FROM nvidia/cuda:10.0-cudnn7-devel-ubuntu16.04 as devtoolset
30 FROM nvidia/cuda:10.0-cudnn7-devel-ubuntu16.04
/external/arm-trusted-firmware/plat/nvidia/tegra/common/
Dtegra_common.mk8 PLAT_INCLUDES := -Iplat/nvidia/tegra/include/drivers \
9 -Iplat/nvidia/tegra/include/lib \
10 -Iplat/nvidia/tegra/include
15 TEGRA_COMMON := plat/nvidia/tegra/common
16 TEGRA_DRIVERS := plat/nvidia/tegra/drivers
17 TEGRA_LIBS := plat/nvidia/tegra/lib
/external/tensorflow/tensorflow/tools/ci_build/builds/
Dprint_build_info.sh71 if [[ -f /proc/driver/nvidia/version ]]; then
72 NVIDIA_DRIVER_VER=$(head -1 /proc/driver/nvidia/version | awk '{print $(NF-6)}')
77 if [[ ! -z $(which nvidia-debugdump) ]]; then
78 CUDA_DEVICE_COUNT=$(nvidia-debugdump -l | grep "^Found [0-9]*.*device.*" | awk '{print $2}')
79 …CUDA_DEVICE_NAMES=$(nvidia-debugdump -l | grep "Device name:.*" | awk '{print substr($0, index($0,\
/external/angle/infra/specs/
Dwaterfalls.pyl64 'linux-nvidia': {
74 'linux-nvidia-perf': {
101 'mac-nvidia': {
130 'win10-x64-nvidia': {
140 'win10-x64-nvidia-perf': {
149 'win7-x64-nvidia': {
/external/llvm-project/llvm/utils/docker/nvidia-cuda/
DDockerfile1 #===- llvm/utils/docker/nvidia-cuda/build/Dockerfile ---------------------===//
9 FROM nvidia/cuda:8.0-devel as builder
29 FROM nvidia/cuda:8.0-devel
/external/angle/src/third_party/libXNVCtrl/
DREADME.angle3 URL: http://cgit.freedesktop.org/~aplattner/nvidia-settings/
12 The current version is pulled from nvidia-settings-302.17.
/external/llvm-project/llvm/test/CodeGen/NVPTX/
Dconvergent-mir-call.ll1 ; RUN: llc -mtriple nvptx64-nvidia-cuda -stop-after machine-cp -o - < %s 2>&1 | FileCheck %s
6 target triple = "nvptx64-nvidia-cuda"
Dspeculative-execution-divergent-target.ll4 ; RUN: opt < %s -S -mtriple=nvptx-nvidia-cuda -speculative-execution | \
6 ; RUN: opt < %s -S -mtriple=nvptx-nvidia-cuda -speculative-execution \
Dconstant-vectors.ll3 target triple = "nvptx-nvidia-cuda"
/external/llvm/test/CodeGen/NVPTX/
Dconvergent-mir-call.ll1 ; RUN: llc -mtriple nvptx64-nvidia-cuda -stop-after machine-cp -o - < %s 2>&1 | FileCheck %s
6 target triple = "nvptx64-nvidia-cuda"
Dspeculative-execution-divergent-target.ll4 ; RUN: opt < %s -S -mtriple=nvptx-nvidia-cuda -speculative-execution | \
6 ; RUN: opt < %s -S -mtriple=nvptx-nvidia-cuda -speculative-execution \
Dconstant-vectors.ll3 target triple = "nvptx-nvidia-cuda"
/external/skqp/src/compute/hs/vk/bench/
Dmake_bench.bat15 ../nvidia/sm_35/u32/hs_nvidia_sm35_u32.c ^
16 ../nvidia/sm_35/u64/hs_nvidia_sm35_u64.c ^
DMakefile12 ../nvidia/sm_35/u32/hs_nvidia_sm35_u32.c \
13 ../nvidia/sm_35/u64/hs_nvidia_sm35_u64.c \
/external/igt-gpu-tools/tests/
Dprime_nv_pcopy.c544 rect intel, nvidia, linear; in test1_micro() local
565 nv_bo_alloc(&bo_nvidia, &nvidia, w, h, 0x10, -1, NOUVEAU_BO_VRAM); in test1_micro()
581 perform_copy(bo_nvidia, &nvidia, 0, 0, bo_linear, &linear, 0, 0, nvidia.pitch, nvidia.h); in test1_micro()
585 perform_copy(bo_intel, &intel, dst_x, dst_y, bo_nvidia, &nvidia, src_x, src_y, w, h); in test1_micro()
681 rect intel, nvidia, linear; in test3_base() local
698 nv_bo_alloc(&bo_nvidia, &nvidia, 300 * cpp, 300, tile_src, -1, NOUVEAU_BO_VRAM); in test3_base()
707 perform_copy(bo_nvidia, &nvidia, 0, 0, bo_linear, &linear, 0, 0, nvidia.pitch, nvidia.h); in test3_base()
711 perform_copy(bo_intel, &intel, dst_x, dst_y, bo_nvidia, &nvidia, src_x, src_y, w, h); in test3_base()
/external/arm-trusted-firmware/plat/nvidia/tegra/
Dplatform.mk8 SOC_DIR := plat/nvidia/tegra/soc/${TARGET_SOC}
58 include plat/nvidia/tegra/common/tegra_common.mk
/external/llvm-project/flang/
DCODE_OWNERS.TXT13 E: sscalpone@nvidia.com
17 E: eschweitz@nvidia.com
/external/ImageMagick/m4/
Dax_have_opencl.m4113 LIBS="$save_LIBS -L/usr/lib64/nvidia -L/usr/lib/nvidia -lOpenCL"
129 LIBS_CL="$save_LIBS -L/usr/lib64/nvidia -L/usr/lib/nvidia -lOpenCL"
/external/tensorflow/tensorflow/python/compiler/tensorrt/
DREADME.md15 https://docs.nvidia.com/deeplearning/dgx/index.html#installing-frameworks-for-jetson
30 [Verified Models](https://docs.nvidia.com/deeplearning/frameworks/tf-trt-user-guide/index.html#veri…
34 [TF-TRT documentation](https://docs.nvidia.com/deeplearning/frameworks/tf-trt-user-guide/index.html)
/external/llvm-project/llvm/docs/
DDocker.rst12 We currently provide Dockerfiles with ``debian8`` and ``nvidia-cuda`` base images.
133 We currently provide two images: debian8-based and nvidia-cuda-based. They
135 preinstalled binaries. Debian8 is very minimal, nvidia-cuda is larger, but has
143 you should choose nvidia-cuda-based image and use `nvidia-docker
144 <https://github.com/NVIDIA/nvidia-docker>`_ to run your docker containers. Note
145 that you don't need nvidia-docker to build the images, but you need it in order
/external/google-breakpad/src/tools/windows/converter_exe/
Dwinsymconv_test.cmd38 -n https://driver-symbols.nvidia.com ^
57 -n https://driver-symbols.nvidia.com ^
Dwinsymconv.cmd40 -n https://driver-symbols.nvidia.com ^
59 -n https://driver-symbols.nvidia.com ^

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