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 ...
GitHub

Spring Boot REST API

Java 17 or higher Maven 3.6 or higher PostgreSQL 12 or higher Redis 6 or higher IDE (IntelliJ IDEA, Eclipse, or VS Code) src/main/java/com/rskworld ...
Outlookindia

Why Is Caching Challenging In Constantly Changing Blockchain States?

Blockchain network architectures have been designed with the following properties: decentralized, transparent, and dynamic. Every new block changes the following information: a block’s contribution to ...
IEEE

Deep Reinforcement Learning-Based Joint Caching and Routing in AI-Driven Networks

Abstract: To reduce redundant traffic transmission in both wired and wireless networks, optimal content placement problem naturally occurring in many applications is studied. In this paper, ...
IEEE

Caching Optimization in User-Centric Networks: A Stochastic Geometry Perspective

Abstract: User-centric network (UCN) is regarded as a promising technology to provide users with high network capacity through a cluster of cooperative base stations (BSs). However, to support many-to ...