On Jan. 26, 2026, the Submillimeter Array (SMA) on Maunakea crossed an important threshold for time-domain astronomy. For the ...
For the first time, a research team has demonstrated an artificial intelligence semiconductor technology that integrates the ...
Abstract: Sparse matrix multiplication is widely used in various practical applications. Different accelerators have been proposed to speed up sparse matrix-dense vector multiplication (SpMV), sparse ...
===== Benchmarks for 3×3 Float64 matrices ===== Matrix multiplication -> 5.9x speedup Matrix multiplication (mutating) -> 1.8x speedup Matrix addition -> 33.1x ...
Researchers at Tsinghua University developed the Optical Feature Extraction Engine (OFE2), an optical engine that processes data at 12.5 GHz using light rather than electricity. Its integrated ...
TPUs are Google’s specialized ASICs built exclusively for accelerating tensor-heavy matrix multiplication used in deep learning models. TPUs use vast parallelism and matrix multiply units (MXUs) to ...
Analog computers are systems that perform computations by manipulating physical quantities such as electrical current, that map math variables, instead of representing information using abstraction ...
Abstract: Real-time applications like audio signal processing and wireless communication highly demand the need for powerful and efficient multiplier and accumulator units (MACs) for achieving high ...
The original version of this story appeared in Quanta Magazine. Moore’s law is already pretty fast. It holds that computer chips pack in twice as many transistors every two years or so, producing ...
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