AOCL-DLP (Deep Learning Primitives) is a high-performance library that provides optimized deep learning primitives for AMD processors. The library implements Low Precision GEMM (LPGEMM) operations for machine learning applications with support for multiple data types, post-operations, and quantization techniques. Select kernels have been optimized for AMD “Zen”-based processors, including AMD EPYC™, AMD Ryzen™, and AMD Ryzen™ Threadripper™ processors, leveraging AVX2, AVX512, AVX512_VNNI, and AVX512_BF16 instruction sets.
AOCL-DLP provides APIs for GEMM operations with various precision formats, comprehensive post-operations for fused computations, batch GEMM support, symmetric quantization routines, and parallel execution via OpenMP.
This chapter provides detailed information regarding AOCL-DLP installation, building AOCL-DLP from source, usage examples, performance tuning, integration into applications, and troubleshooting. For the full API documentation, please refer to the latest AOCL-DLP documentation at