Abstract: Efficiently synthesizing an entire application that consists of multiple algorithms for hardware implementation is a very difficult and unsolved problem. One of the main challenges is the ...
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 ...
Novavax secures a non-exclusive licensing deal with Pfizer, validating Matrix-M's platform value and shifting NVAX toward a technology provider model. NVAX receives $30M upfront, a potential $500M in ...
In order to find the minimizer of Ⅼ using gradient descent with fixed stepsize, we create a function called gd. This function takes the arguments: start, f, gradient, step_size, maxiter, and tolerance ...
CUDA-L2 is a system that combines large language models (LLMs) and reinforcement learning (RL) to automatically optimize Half-precision General Matrix Multiply (HGEMM) CUDA kernels. CUDA-L2 ...
d-Matrix completed a US$275 million Series C round in early November, raising its valuation to US$2 billion, and is speeding up the commercialisation of its 3D In-Memory Compute (3D IMC) technology ...
Abstract: Sparse Matrix-Matrix Multiplication (SpMM) is a widely used algorithm in Machine Learning, particularly in the increasingly popular Graph Neural Networks (GNNs). SpMM is an essential ...
BOSTON — A federal judge indicated Thursday she is inclined to take steps to ensure that federal food assistance keeps flowing to 42 million Americans who depend on it. Trump administration officials ...
Last year, onlookers observed a startling site on China’s Qiantang River: waves forming a grid-like pattern. Dubbed the “matrix tide,” this complex wave pattern was caused by the river’s famed tidal ...
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