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60% MatMul Performance Bug in cuBLAS on RTX 5090
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60% MatMul Performance Bug in cuBLAS on RTX 5090

RTX 5090 上 cuBLAS 的 60% 矩陣乘法效能漏洞

cuBLAS is dispatching an inefficient kernel for every batched FP32 workload, leaving ~60% of your RTX GPU's compute power on the table. The bug affects everything from 256×256 to 8192×8192×8 matrix operations and likely hits all RTX non-Pro GPUs. Tested on RTX 5090 with the latest CUDA 13.2.51, cuBLAS 13.3.0, and driver 595.58.03—older versions perform even worse. A custom kernel implementation shows dramatic improvements across various workloads, with some cases running 2x faster than cuBLAS.

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Keywords

performance bugMatMulbatched operationsFP32GPU optimizationkernel efficiencycompute utilization

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