OpenSolvers explores how open-source scientific software runs on real hardware — starting with RISC-V boards and the tools that make that practical (EESSI, OpenBLAS, and friends). This site documents what we learn along the way.

What we’re working on

We benchmark scientific libraries and applications on consumer RISC-V boards through the EESSI stack — from BLAS kernels up to full app runs — swapping fixed OpenBLAS builds via FlexiBLAS without rebuilding downstream code.

Recent highlights on the Orange Pi RV2 (SpaceMiT X60, RVV): fixing an OpenBLAS gemv_n bug restores correctness across BLAS, LAPACK, ELPA, and HPL — with patched RVV reaching 10.53 GFLOP/s on Linpack and 1.58× on a dense eigensolve.

Scientific libs

Library-level probes — performance and numerical correctness:

• BLAS — OpenBLAS improvements (U74 tuned kernel, X60 RVV gemv_n fix) and difftest / bench_dgemm verification
• LAPACK — NumPy dgemm and eigvalsh as a real SciPy-stack probe
• ELPA — dense eigensolver mixing BLAS-2 and BLAS-3 (CP2K / VASP class workloads)

Apps

End-to-end application benchmarks on the same boards and EESSI toolchain:

• HPL — High Performance Linpack; cross-board summary and A/B configs from opensolvers/benchmarks

Boards

• StarFive VisionFive 2 — JH7110 SoC, 4× SiFive U74 (rv64gc). U74 OpenBLAS tuning: HPL 3.13 → 5.28 GFLOP/s.
• Orange Pi RV2 — SpaceMiT K1, 8× X60 (RVV). Fixed OpenBLAS: HPL FAILED (nan) → 10.53 GFLOP/s; ELPA 34.81 s (vs 54.92 s scalar).
• Banana Pi F3 — same K1 / X60 SoC; same fixes apply, peak results not yet recorded.

Use the menu above to jump to a board, app, or scientific lib page.