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New 3D-stacked memory tech seeks to dethrone HBM in AI inference — d-Matrix claims 3DIMC will be 10x faster and 10x more efficient
Santa Clara-based startup d-Matrix looks to replace HBM in AI inference with 3DIMC, or 3D digital in-memory-compute. The ...
Annals of Mathematics, a distinguished journal of research papers in pure mathematics, was founded in 1884. Annals of Mathematics is published bimonthly with the cooperation of Princeton University ...
On a B200, the nvjet_tst_16x64_64x16_4x1_v_bz_TNN kernel is used, and it takes roughly 8.1 microseconds. On a H200, the nvjet_tst_64x8_64x16_4x1_v_bz_TNT kernel is ...
This project implements various sparse matrix computations in CUDA and C++. It includes conversion routines between sparse matrix formats and efficient CUDA kernels for Sparse Matrix-Vector ...
Abstract: A mixed-precision analog compute-in-memory (Mix-ACIM) is presented for mixed-precision vector-matrix multiplication (VMM). The design features an all-analog current-domain fixed-point (FxP) ...
The inspiration for this column comes not from the epic 1999 film The Matrix, as the title may suggest, but from an episode of Sean Carroll’s Mindscape podcast that I listened to over the summer. The ...
Abstract: Machine Learning and AI approaches have stretched traditional hardware to its limits. In-hardware computing is a novel approach that aims to run Matrix-Vector Multiplication operations ...
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