Revision fbe030b0dcfdc336eb10b80cbb28c37f3e3496b2 authored by KeDengMS on 10 November 2017, 19:48:16 UTC, committed by KeDengMS on 10 November 2017, 19:48:16 UTC
On Linux: sudo mkdir /usr/local/mklml sudo wget https://github.com/01org/mkl-dnn/releases/download/v0.11/mklml_lnx_2018.0.1.20171007.tgz sudo tar -xzf mklml_lnx_2018.0.1.20171007.tgz -C /usr/local/mklml On Windows: Create a directory on your machine to hold MKLML, e.g. mkdir c:\local\mklml Download the file [mklml_win_2018.0.1.20171007.zip](https://github.com/01org/mkl-dnn/releases/download/v0.11/mklml_win_2018.0.1.20171007.zip). Unzip it into your MKLML path, creating a versioned sub directory within. Set the environment variable `MKLML_PATH` to the versioned sub directory, e.g. setx MKLML_PATH c:\local\mklml\mklml_win_2018.0.1.20171007 This change also enables CPU convolution forward/backward using MKL, which leads to ~4x speedup in AlexNet training.
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File | Mode | Size |
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cntk-binary-drop | ||
devInstall | ||
docker | ||
README.md | -rw-r--r-- | 330 bytes |
build-and-test | -rwxr-xr-x | 12.8 KB |
check-git-head.sh | -rwxr-xr-x | 1.9 KB |
generate_build_info | -rwxr-xr-x | 5.4 KB |
get-datasets.sh | -rwxr-xr-x | 1.0 KB |
make_binary_drop_linux | -rwxr-xr-x | 7.4 KB |
make_binary_drop_windows.ps1 | -rw-r--r-- | 5.1 KB |
make_samples_zip.ps1 | -rw-r--r-- | 1.4 KB |
msvc_collect_coverage.py | -rwxr-xr-x | 2.4 KB |
run_boost_unit_tests.py | -rwxr-xr-x | 1.5 KB |
samples.json | -rw-r--r-- | 27.8 KB |
test-samples-json.ps1 | -rw-r--r-- | 3.3 KB |
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