
Developed RISC-V Vector (RVV) support for rv64gcv targets in the JoltPhysics repository, focusing on enabling efficient vectorized physics computations on RISC-V hardware. The work involved implementing sizeless RVV vector types as arrays of scalars and introducing a new RISCVVector.h header with helper functions for vector shuffling, modeled after ARMNeon.h patterns. By integrating RVV into core mathematical operations, the developer improved both performance and compatibility for RISC-V architectures. Utilizing C++ and low-level programming techniques, the contribution established reusable vector utilities and aligned with a multi-architecture performance roadmap, laying a foundation for future vectorization efforts across platforms.
Month: 2026-03 — Focused on expanding platform support by delivering RISC-V Vector (RVV) support for rv64gcv targets in JoltPhysics. Implemented sizeless RVV vector types stored as arrays of scalars, added RISCVVector.h with helper functions for vector shuffling, and integrated RVV into existing mathematical operations to improve performance and compatibility on RISC-V hardware. This work lays the groundwork for broader vectorization across architectures and involved collaboration to align with the multi-arch performance roadmap. No major bugs reported; primary value delivered is enabling efficient vectorized physics computations on RVV-capable targets and establishing reusable vector utilities for future work.
Month: 2026-03 — Focused on expanding platform support by delivering RISC-V Vector (RVV) support for rv64gcv targets in JoltPhysics. Implemented sizeless RVV vector types stored as arrays of scalars, added RISCVVector.h with helper functions for vector shuffling, and integrated RVV into existing mathematical operations to improve performance and compatibility on RISC-V hardware. This work lays the groundwork for broader vectorization across architectures and involved collaboration to align with the multi-arch performance roadmap. No major bugs reported; primary value delivered is enabling efficient vectorized physics computations on RVV-capable targets and establishing reusable vector utilities for future work.

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