Uploaded November 2025 | Updated September 2026, 2 weeks ago
Pushing the Packed SIMD Extension Over the Line: An Update on the Progress of Key RISC-V Extension - Rich Fuhler, Andes
Scalar SIMD DSP (Single Instruction, Multiple Data Digital Signal Processing) instructions are essential for modern processor architectures, enabling efficient, low-power computation on small-width data in scalar registers. Unlike traditional vector SIMD, scalar SIMD targets latency-sensitive tasks like audio/image processing, filtering, and fixed-point arithmetic in embedded, real-time, and edge AI applications. These instructions improve performance in tight scalar loops using saturated arithmetic, MACs, and bit manipulation, while minimizing area and power. Adopted in ARM Cortex-M, RISC-V DSP, and Apple Silicon, scalar SIMD DSP bridges general-purpose CPUs and dedicated DSPs, crucial for mobile, IoT, automotive, and consumer devices. This paper explores architectural drivers, market relevance, and implementations, emphasizing its role in efficient signal processing. Our ongoing work in the Packed SIMD Task Group supports this with preliminary mnemonics, opcodes, POC LLVM/binutils support, SAIL models, and draft documentation. Workstreams run in parallel to accelerate development.
Pushing the Packed SIMD Extension Over the Line: An Update on the Progress of Key RISC-V Extension - Rich Fuhler, Andes
Scalar SIMD DSP (Single Instruction, Multiple Data Digital Signal Processing) instructions are essential for modern processor architectures, enabling efficient, low-power computation on small-width data in scalar registers. Unlike traditional vector SIMD, scalar SIMD targets latency-sensitive tasks like audio/image processing, filtering, and fixed-point arithmetic in embedded, real-time, and edge AI applications. These instructions improve performance in tight scalar loops using saturated arithmetic, MACs, and bit manipulation, while minimizing area and power. Adopted in ARM Cortex-M, RISC-V DSP, and Apple Silicon, scalar SIMD DSP bridges general-purpose CPUs and dedicated DSPs, crucial for mobile, IoT, automotive, and consumer devices. This paper explores architectural drivers, market relevance, and implementations, emphasizing its role in efficient signal processing. Our ongoing work in the Packed SIMD Task Group supports this with preliminary mnemonics, opcodes, POC LLVM/binutils support, SAIL models, and draft documentation. Workstreams run in parallel to accelerate development.
