Convolutional neural networks (CNNs) rely heavily on matrix–vector multiplication (MVM), but most existing photonic MVM chips use only one or two optical degrees of freedom (DoFs), limiting their ...
Researchers have demonstrated a ferroelectric memory chip that performs both random sampling and AI computation, paving the ...
AMD and Intel have now published a full technical specification for ACE — AI Compute Extensions — the most significant overhaul to x86 AI compute in the architecture's history, co-authored by eight ...
When it comes to designing wearable devices for women there are a various factors that need to be taken into account.
Right off the bat, let’s give a shout out to the mathematician propeller-heads who create the transformations that make it possible to do all kinds of high performance computing to simulate, model, ...
Abstract: In this paper, we present a 10T SRAM compute-in memory (CiM) macro to process the multiplication-accumulation (MAC) operations between ternary-inputs and binary-weights. In the proposed 10T ...
Sparse matrices, which are common in scientific applications, are matrices in which most elements are zero. To save space and running time it is critical to only store the nonzero elements. A standard ...
Abstract: Exploiting spatial and temporal localities is investigated for efficient row-by-row parallelization of general sparse matrix-matrix multiplication (SpGEMM) operation of the form C=AB on many ...
For the first time, a research team has demonstrated an artificial intelligence semiconductor technology that integrates the ...
Earlier this spring, AMD, Broadcom, Meta Platforms, Microsoft, Nvidia, and OpenAI formed the Optical Compute Interconnect ...
Fault-tolerant quantum simulation just got 250 times cheaper to run. QuEra Computing and Los Alamos published an architecture ...
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