新方法预测任意GPU运行LLM的功耗与延迟，助力数据中心高效部署。
arXiv:2607.02391v1 Announce Type: cross Abstract: Large Language Model (LLM) inference workloads are a rapidly growing contributor to data center ener…
基于MSDF数字串行算术的FPGA方案，在CNN加速中实现高能效与低资源占用，边缘计算场景的实用新思路。
arXiv:2606.25562v1 Announce Type: cross Abstract: This paper presents an energy-efficient hardware acceleration of the convolutional layers in the U-N…
LLM服务节能新方案：利用预填充/解码解耦架构，动态GPU频率控制实现36.3%能耗节省
Article URL: https://supercomputing-system-ai-lab.github.io/projects/voltana/ Comments URL: https://news.ycombinator.com/item?id=48655520 Points: 2 # …
提出AgentStop方法，在消费设备上提前终止本地AI代理以节省能耗，兼顾隐私、成本与能效优化。
arXiv:2605.15206v1 Announce Type: cross Abstract: Autonomous agents powered by large language models (LLMs) are increasingly used to automate complex,…