ENIAD:面向web级ai大数据服务的可重构近数据处理架构

Jialiang Zhang, JingJane Li
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引用次数: 1

摘要

为了满足人工智能大数据服务激增的需求,云供应商正在转向特定领域的加速器,以提高效率、可扩展性和性能。ENIAD是首个为人工智能大数据提供实时服务的端到端基础设施,可在数据中心规模上加速深度神经网络推理和十亿级索引。利用近数据计算、可重构计算和快速/敏捷的硬件部署流程,ENIAD以低批量规模高效率地提供最先进的在线构建索引服务。系统的核心是一个高性能、索引(数据)适应性强的FPGA软处理器,与最先进的CPU和GPU架构相比,它能够处理10倍大的索引大小,延迟降低14倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ENIAD: A Reconfigurable Near-data Processing Architecture for Web-Scale AI-enriched Big Data Service
To meet the surging demands required by AI-enriched Big Data services, cloud vendors are turning toward domain specific accelerators for improved efficiency, scalability and performance. ENIAD, the first end-to-end infrastructure for AI-enriched Big Data serving in real time, accelerates both deep neural network inferencing and billion-scale indexing at the data-center scale. Exploiting near- data computation, reconfigurable computing and rapid/agile hardware deployment flow, ENIAD serves state-of-the-art, online built indexing service with high efficiency at low batch sizes. A high-performance, index (data)-adaptable FPGA soft processor is at the heart of the system and able to serve 10x larger index size with 14x lower latency compared to state-of-the-art CPU and GPU architectures.
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