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SimSIMD is expanding and becoming closer to a fully-fledged BLAS library. BLAS level 1 for now, but it's a start! SimSIMD will prioritize mixed and low-precision vector math, favoring modern AI workloads. For image & media processing workloads, the new
fma
andwsum
kernels approach 65 GB/s per core on Intel Sapphire Rapids. That's 100x faster than the serial code foru8
inputs withf32
scaling and accumulation.Contains the following element-wise operations:
In NumPy terms:
This tiny set of operations is enough to implement a wide range of algorithms:
Benchmarks
On Intel Sapphire Rapids: