This README file contains the following sections:
- OVERVIEW
- SOFTWARE TOOLS AND SYSTEM REQUIREMENTS
- DESIGN FILE HIERARCHY
- BUILD GEMX-BASED EXAMPLE APPLICATIONS
- SUPPORT
- LICENSE AND CONTRIBUTING TO THE REPOSITORY
- ACKNOWLEDGEMENTS
- REVISION HISTORY
GEMX is a General Matrix Operation library, which is used for accelerating BLAS-like matrix operations on SDAccel supported FPGA cards. This library includes three components: an engine library, a host code compiler and an application or system building environment. The engine library consists of a set of C++ templates with BLAS-like function interfaces for realizing matrix operations on FPGAs. The host code compiler compiles the host code matrix function calls into a sequence of instructions for triggering matrix operations on FPGAs. The building environment utilizes GNU make flow to automate the FPGA and host code image generation process. It also allows users to configure different aspects of the system, e.g. FPGA platform, number of engines implemented in the FPGA image and etc. For detailed information about GEMX engine design, please refer to GEMX_ENGINE_UG
Board | DSA Name | Software Version |
---|---|---|
Xilinx KCU1500 | xilinx:kcu1500:dynamic:5_0 | SDx 2017.4 |
Xilinx VU9P | xilinx:vcu1525:dynamic:5_0 | SDx 2017.4 |
Source code for building FPGA and host code images is located in the gemx/src directory. boost/ directory provides implementation for OpenCL functions used to instantiate an accelerator, trasmit data between the host and the accelerator and etc. Please refer to gemx_api_gemm.cpp to see its usage. gemx/Makefile is used to build FPGA and host images with different configurations. gemx/hls_config.tcl is used to configure the hls compilation options. gemx/run-hls.tcl is used to create vivado_hls project from cpu emulation results. gemx/data includs input sparse matrices' data.
Following four GEMX-BASED applications are created for xilinx:vcu1525:dynamic:5_0 DSA to demonstrate the GEMX engine usage.
- gemm_perf: dense matrix matrix multiplication performance measurement
- spmv_perf: sparse matrix vector multiplication performance measurement
- gemm_test_python: python-based densen matrix matrix multiplication testing
- gemx_func_test: GEMX engine testing in sofware emulation
Before compiling and building FPGA and host images, make sure SDAccel 2017.4 envioronment variales are set up properly and navigate to gemx/ directory, and enter command:
./run_app.sh
enter one of the four application names when the command line prompts for input.
For more information about SDAccel check the SDAccel User Guides
For questions and to get help on this project or your own projects, visit the SDAccel Forums.
The source for this project is licensed under the 3-Clause BSD License
To contribute to this project, follow the guidelines in the Repository Contribution README
This example is written by developers at
Date | README Version | Description |
---|---|---|
Oct2017 | 1.0 | Initial Xilinx Release |
Mar2018 | 2.0 | Updated to SDx 2017.4 |