{"id":166444,"date":"2006-01-01T00:00:00","date_gmt":"2006-01-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/area-performance-trade-offs-in-tiled-dataflow-architectures\/"},"modified":"2018-10-16T20:18:01","modified_gmt":"2018-10-17T03:18:01","slug":"area-performance-trade-offs-in-tiled-dataflow-architectures","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/area-performance-trade-offs-in-tiled-dataflow-architectures\/","title":{"rendered":"Area-Performance Trade-offs in Tiled Dataflow Architectures"},"content":{"rendered":"<p>Tiled architectures, such as RAW, SmartMemories, TRIPS, and WaveScalar, promise to address several issues facing conventional processors, including complexity, wire-delay, and performance. The basic premise of these architectures is that larger, higher-performance implementations can be constructed by replicating the basic tile across the chip. This paper explores the area-performance trade-offs when designing one such tiled architecture, WaveScalar. We use a synthesizable RTL model and cycle-level simulator to perform an area\/performance pareto analysis of over 200 WaveScalar processor designs ranging in size from 19mm<sup>2<\/sup> to 575mm<sup>2<\/sup> and having a 22 FO4 cycle time. We demonstrate that, for multi-threaded workloads, WaveScalar performance scales almost ideally from 19 to 101mm <sup>2<\/sup> when optimized for area efficiency and from 44 to 202mm<sup>2<\/sup> when optimized for peak performance. Our analysis reveals that WaveScalar&#8217;s hierarchical interconnect plays an important role in overall scalability, and that WaveScalar achieves the same (or higher) performance in substantially less area than either an aggressive out-of-order superscalar or Sun&#8217;s Niagara CMP processor.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Tiled architectures, such as RAW, SmartMemories, TRIPS, and WaveScalar, promise to address several issues facing conventional processors, including complexity, wire-delay, and performance. The basic premise of these architectures is that larger, higher-performance implementations can be constructed by replicating the basic tile across the chip. This paper explores the area-performance trade-offs when designing one such tiled [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":null,"msr_publishername":"IEEE Computer Society","msr_publisher_other":"","msr_booktitle":"Proceedings of the 33rd Annual International Symposium on Computer Architecture","msr_chapter":"","msr_edition":"Proceedings of the 33rd Annual International Symposium on Computer Architecture","msr_editors":"","msr_how_published":"","msr_isbn":"0-7695-2608-X","msr_issue":"","msr_journal":"","msr_number":"","msr_organization":"","msr_pages_string":"314\u2013326","msr_page_range_start":"314","msr_page_range_end":"326","msr_series":"ISCA '06","msr_volume":"","msr_copyright":"","msr_conference_name":"Proceedings of the 33rd Annual International Symposium on Computer Architecture","msr_doi":"10.1109\/ISCA.2006.10","msr_arxiv_id":"","msr_s2_paper_id":"","msr_mag_id":"","msr_pubmed_id":"","msr_other_authors":"Steven Swanson, Martha Mercaldi, Ken Michelson, Andrew Petersen, Andrew Schwerin, Mark Oskin, Susan J. 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