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NVIDIA Speeds Up Scientific Simulations With New cuBLAS Algorithms
NVIDIA Technical blog ·
At a glance
NVIDIA added new algorithms to its cuBLAS library that speed up the high-precision matrix multiplication used in scientific simulations. The results keep their full accuracy. The change is available in CUDA Toolkit 13.4.2.
Key points
- The new method splits large numbers into small integer pieces, computes them on the GPU's integer units, and then recombines them.
- Ozaki-II needs fewer integer multiplications than the earlier Ozaki-I method.
- The 2M method cuts complex matrix multiplication from four real multiplications to two.
- On NVIDIA GB200, DGEMM reportedly runs about 3.9 times faster than the native method.
Why it matters
Scientific simulations, such as those for climate, new materials, and drug discovery, spend most of their time on matrix multiplication. Speeding up this step without losing accuracy can shorten research time and lower costs.
Original source
Faster Scientific Simulations with New FP64 Algorithms in NVIDIA cuBLAS
NVIDIA Technical blog · Nov 14, 07:13 KST
Read on NVIDIA Technical blog ↗AI summarized the original article. Check the original for accuracy. Copyright belongs to NVIDIA Technical blog.
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