MIT researchers have designed silicon structures that can perform calculations in an electronic device using excess heat instead of electricity. These tiny structures could someday enable more ...
“We must strive for better,” said IBM Research chief scientist Ruchir Puri at a conference on AI acceleration organised by the computer company and the IEEE in November. He expects almost all language ...
This paper came across my feed that implements sparse matrix-vector multiplication. Sparse matrix-vector multiplication (SpMV) is a fundamental operation in scientific computing, data analysis, and ...
SANTA CLARA, Calif.--(BUSINESS WIRE)--Further expanding SiFive’s lead in RISC-V AI IP, the company today launched its 2nd Generation Intelligence™ family, featuring five new RISC-V-based products ...
Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Traditional caching fails to stop "thundering ...
ABSTRACT: Node renumbering is an important step in the solution of sparse systems of equations. It aims to reduce the bandwidth and profile of the matrix. This allows for the speeding up of the ...
Hand-tuned WebAssembly implementations for efficient execution of web-based sparse computations including Sparse Matrix-Vector Multiplication (SpMV), sparse triangular solve (SpTS) and other useful ...
The world of scientific computing and machine learning heavily relies on tensor computations. Many tensors encountered in physics, chemistry, linear algebra, and graph theory exhibit symmetry and ...
Abstract: Structured sparsity has been proposed as an efficient way to prune the complexity of Machine Learning (ML) applications and to simplify the handling of sparse data in hardware. Accelerating ...
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