IEEE

Efficient KV Cache Spillover Management on Memory-Constrained GPU for LLM Inference

Abstract: The rapid growth of model parameters presents a significant challenge when deploying large generative models on GPU. Existing LLM runtime memory management solutions tend to maximize batch ...
Morningstar

Direct Genome-Scale Mapping of Endonuclease Activity of the Human LINE-1 ORF2p Endonuclease

Nabsys and the Research Lab of Dr. Martin Taylor, Brown University, Present Data Using the OhmX™ Platform at AGBT 2026 EGM enables the direct detection of endonuclease activity at the genome scale by ...
GitHub

A high-performance, distributed in-memory cache library for Go that synchronizes local LFU/LRU caches across multiple service instances using Redis as a backing store and pub ...

The distributed-cache library uses a two-level caching architecture with local in-process caches synchronized via Redis pub/sub. When a pod sets a value, it's stored locally and in Redis, then ...
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 ...
VentureBeat

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

Researchers at Nvidia have developed a technique that can reduce the memory costs of large language model reasoning by up to eight times. Their technique, called dynamic memory sparsification (DMS), ...