Posts tagged Compiler

Reading AMDGCN ISA

For an application developer it is often helpful to read the Instruction Set Architecture (ISA) for the GPU architecture that is used to perform its computations. Understanding the instructions of the pertinent code regions of interest can help in debugging and achieving performance optimization of the application.

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Application portability with HIP

Many scientific applications run on AMD-equipped computing platforms and supercomputers, including Frontier, the first Exascale system in the world. These applications, coming from a myriad of science domains, were ported to run on AMD GPUs using the Heterogeneous-compute Interface for Portability (HIP) abstraction layer. HIP enables these High-Performance Computing (HPC) facilities to transition their CUDA codes to run and take advantage of the latest AMD GPUs. The effort involved in porting these scientific applications varies from a few hours to a few weeks and largely depends on the complexity of the original source code. Figure 1 shows several examples of applications that have been ported and the corresponding porting effort.

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C++17 parallel algorithms and HIPSTDPAR

The C++17 standard added the concept of parallel algorithms to the pre-existing C++ Standard Library. The parallel version of algorithms like std::transform maintain the same signature as the regular serial version, except for the addition of an extra parameter specifying the execution policy to use. This flexibility allows users that are already using the C++ Standard Library algorithms to take advantage of multi-core architectures by just introducing minimal changes to their code.

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AMD matrix cores

Note: This blog was previously part of the AMD lab notes blog series.

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