Parallel computing with RISC-V vectors (lecture)

About

For faster computing it is necessary to utilize data parallelism. The tools available for programmers for parallel computing depend on hardware and CPUs architecture. The RISC-V architecture provides a vector processor style Single Instruction, Multiple Data (SIMD) instruction. The proposed 1 hour lecture will include: - Concept of parallel data processing. Classification of various approaches. - Overview of an array processor and vector processor approach. How these theoretical approaches are used for vectorization in CPUs and GPUs. - Description of how SIMD is implemented in x86 architecture; its features, advantages and problems. - Description of how RISC-V "V" extension is implementing scalable vectorization; it's features, problems and advantages over x86 architecture approach. - Examples of vectorizations done by compiler and necessary manual vectorizations.

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