Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...
We took this version of HeCBench and are modifying it to build the CUDA and OMP codes to gather their roofline performance data. So far we have a large portion of the CUDA and OMP codes building ...
Abstract: Sparse-sparse matrix multiplication (SpGEMM) is a well-studied problem on CPUs, GPUs, accelerators (e.g. FPGAs), and distributed systems. The main computational bottleneck in SpGEMM is the ...
Abstract: Sparse matrix-matrix multiplication (SpMM) is a prevailing kernel in scientific and artificial intelligence applications. However, the irregular memory access behaviors caused by diverse ...
Quantum-inspired adaptive tiling for high-performance matrix multiplication. Uses WKB tunneling physics with the golden ratio to derive optimal tile sizes from real-time CPU state. 15%+ gains on ...
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