cuBLAS adds FP64 algorithms to accelerate scientific simulation
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NVIDIA has added FP64 algorithms to cuBLAS to accelerate two types of high-precision dense matrix multiplication: DGEMM and ZGEMM. NVIDIA says that for many scientific simulations, from molecular chemistry to materials science, most of the execution time is spent on this type of computation. cuBLAS is already widely used by high-performance computing (HPC) and AI applications to accelerate fundamental operations such as GEMM, and the newly added algorithms target the double-precision matrix multiplication scenarios with the highest precision requirements among them.
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- NVIDIA Technical BlogFaster Scientific Simulations with New FP64 Algorithms in NVIDIA cuBLAS
Many scientific simulations, from molecular chemistry to materials science, spend most of their execution time on high-precision dense general matrix multiplications (GEMM), called DGEMM for real 64-bit floating-point numbers and ZGEMM for complex 64-bit floating-point numbers. cuBLAS is widely used by HPC and AI applications to accelerate GEMM and other Basic Linear Algebra Subprograms operations.
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