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 ...

Visualize free body diagrams using vector math in Python to better understand forces and motion. This video shows how vectors represent forces, how they combine mathematically, and how Python helps ...

Researchers create a photochromic fluorescent system that performs optical neural computing and visual output in one step, cutting power use and complexity. (Nanowerk News) The rapid growth of ...

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. Soroosh Khodami discusses why we aren't ready ...

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 ...

A new technical paper titled “Leveraging ASIC AI Chips for Homomorphic Encryption” was published by researchers at Georgia Tech, MIT, Google and Cornell University. “Cloud-based services are making ...

Since homomorphic encryption enables SIMD operations by packing multiple values into a vector of operations and enabling pairwise addition or multiplication operations, one (old) conventional method ...

A new technical paper titled “Scalable MatMul-free Language Modeling” was published by UC Santa Cruz, Soochow University, UC Davis, and LuxiTech. “Matrix multiplication (MatMul) typically dominates ...

Large language models such as ChaptGPT have proven to be able to produce remarkably intelligent results, but the energy and monetary costs associated with running these massive algorithms is sky high.