Facepalm: After consuming virtually the entire GPU market, generative AI and large language models are now putting pressure on DRAM and other mainstream memory products. Consumers are likely to feel ...

Like in nature, development tools for embedded systems form “ecosystems.” Some ecosystems are very self-contained, with little overlap on others, while other ecosystems are very open and broad with ...

A new technical paper titled “Benchmarking of FERAM-Based Memory System by Optimizing Ferroelectric Device Model” was published by researchers at Georgia Tech, imec and National Technical University ...

LWMalloc is an ultra-lightweight dynamic memory allocator designed for embedded systems that is said to outperform ptmalloc used in Glibc, achieving up to 53% faster execution time and 23% lower ...

The lightweight allocator demonstrates 53% faster execution times and requires 23% lower memory usage, while needing only 530 lines of code. Embedded systems such as Internet of Things (IoT) devices ...

Artificial Intelligence (AI) and Machine Learning (ML) applications are driving increased demand for high-performance, low-power memory solutions across consumer, medical, and industrial markets.

TOKYO--(BUSINESS WIRE)--Kioxia Corporation, a world leader in memory solutions, today announced that it has begun sampling (1) new Universal Flash Storage (2) (UFS) Ver. 4.1 embedded memory devices ...

SAN FRANCISCO, July 29 (Reuters) - Enfabrica, a Silicon Valley-based chip startup working on solving bottlenecks in artificial intelligence data centers, on Tuesday released a chip-and-software system ...

MOUNTAIN VIEW, Calif.--(BUSINESS WIRE)--Enfabrica Corporation, an industry leader in high-performance networking silicon for artificial intelligence (AI) and accelerated computing, today announced the ...

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A lot of the attention in the race to meet the processing needs of artificial intelligence and machine learning has focused on state-of-the-art GPUs able to process data at breathtaking speeds. But an ...