Running AI models is turning into a memory game

When we talk about the cost of AI infrastructure, the focus is usually on Nvidia and GPUs -- but memory is an increasingly ...
IEEE

MRAM-Based Cache and In-Memory Computing

Abstract: The rapid advancement in semiconductor technology has led to a significant gap between the processing capabilities of CPUs and the access speeds of memory, presenting a formidable challenge ...

Nvidia’s new technique cuts LLM reasoning costs by 8x without losing accuracy

Nvidia researchers developed dynamic memory sparsification (DMS), a technique that compresses the KV cache in large language models by up to 8x while maintaining reasoning accuracy — and it can be ...
IEEE

Cache-Aware Timing Analysis of Limited Preemption Scheduling With Fixed Preemption Points in Set-Associative Mapping

Abstract: In a limited preemption real-time system with a cache architecture, scheduling analysis must not only consider the execution time of tasks and the blocking of lower-priority tasks, but also ...