NASA Uses RISC-V Vector Spec to Soup Up Space Computers
With the growing demand for applications that require multiple cores and AI, ML, and computer vision capabilities, faster and power-efficient processing is essential. At the same time, companies are looking to simplify design cycles with more portability and re-use, broader extensibility, and more design scalability. The RISC-V Vector spec (RVV) version 1.0, ratified by RISC-V International last December, was created to meet these market requirements and make it easy to implement vector instructions for modern workloads.
Several companies, including SiFive, have solutions already in the market to address the challenges designers face in implementing vector technology.
RISC-V Vector spec benefits
In terms of code size, performance, and area, RVV offers a powerful and extremely efficient alternative to packed-SIMD and GPUs, which are very inefficient for processing large datasets. One problem with packed-SIMD and GPU implementations is that they can require multiple new instructions, so the chip size increases every time new data types are introduced. Additional code is also often required for applications that have specific requirements, increasing code size, and bill of materials costs, along with consuming more power.
With just a few hundred instructions in the Vector ISA, RVV is much smaller than typical packed-SIMD alternatives. Since RVV is so small, it reduces the area that is required for compiled software (the compilers generate very dense code), enabling designs to have better power efficiency and a smaller memory footprint. The good news is code designed and written for packed-SIMD implementations can be easily ported to RISC-V vectors for a seamless transition.
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