mirror of
https://github.com/intel/linux-sgx
synced 2026-06-08 14:49:32 +00:00
9ddec08fb9
Signed-off-by: Zhang Lili Z <lili.z.zhang@intel.com>
41 lines
1.6 KiB
Plaintext
41 lines
1.6 KiB
Plaintext
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Purpose of Deep Neural Network Library (DNNL)
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--------------------------
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The project demonstrates Intel(R) Deep Neural Network Library (DNNL) functions inside Intel(R) SGX environment
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------------------------------------
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How to Build/Execute the Sample Code
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------------------------------------
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1. Install Intel(R) Software Guard Extensions (Intel(R) SGX) SDK for Linux* OS
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2. Build Intel(R) SGX DNNL library.
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a. Download Intel(R) SGX source codes from: https://github.com/intel/linux-sgx
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b. Build the library.
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$ cd ./external/dnnl
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$ make
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3. Install Intel(R) SGX DNNL library and header files.
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a. Copy Intel(R) SGX DNNL lib to the Intel(R) SGX SDK installation directory.
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$ cp "./sgx_dnnl/lib/libsgx_dnnl.a" "$(SGX_SDK)/lib64"
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b. Copy Intel(R) SGX DNNL header files to the Intel(R) SGX SDK header file directory.
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$ cp "./sgx_dnnl/include/*" "$(SGX_SDK)/include"
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4. Make sure your environment is set:
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$ source ${sgx-sdk-install-path}/environment
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5. Build the project with the prepared Makefile:
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a. Hardware Mode, Debug build:
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$ make
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b. Hardware Mode, Pre-release build:
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$ make SGX_PRERELEASE=1 SGX_DEBUG=0
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c. Hardware Mode, Release build:
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$ make SGX_DEBUG=0
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d. Simulation Mode, Debug build:
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$ make SGX_MODE=SIM
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e. Simulation Mode, Pre-release build:
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$ make SGX_MODE=SIM SGX_PRERELEASE=1 SGX_DEBUG=0
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f. Simulation Mode, Release build:
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$ make SGX_MODE=SIM SGX_DEBUG=0
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6. Execute the binary directly:
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$ ./app
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7. Remember to "make clean" before switching build mode
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