Parallel Processor Core for Semantic Search Engines
Parallel and Distributed Processing Workshops and Phd Forum（2011）
摘要
Superior and fast semantic comparison improves the quality of web-search. Semantic comparison involves dot product computation of large sparse tensors which is time consuming and expensive. In this paper we present a low power parallel architecture that consumes only 15.41 Watts and demonstrates a speed-up in the order of 10textsuperscript{5} compared to a contemporary hardware design, and in the order of 10textsuperscript{4} compared to a purely software approach. Such high performance low power architecture can be used in semantic routers to elegantly implement energy efficient distributed search engines.
更多查看译文
关键词
product computation,low power architecture,semantic comparison,semantic search engines,large sparse tensors,semantic routers,parallel processor core,high performance,search engine,software approach,contemporary hardware design,low power parallel architecture,semantic search engine,semantics,tensors,computational modeling,tensile stress,hardware,semantic search,data structures,indexes,search engines,internet
AI 理解论文
溯源树
样例
生成溯源树，研究论文发展脉络
Chat Paper
正在生成论文摘要