{"id":158725,"date":"2009-11-01T00:00:00","date_gmt":"2009-11-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/compiler-assisted-hybrid-operand-communication\/"},"modified":"2018-10-16T19:59:55","modified_gmt":"2018-10-17T02:59:55","slug":"compiler-assisted-hybrid-operand-communication","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/compiler-assisted-hybrid-operand-communication\/","title":{"rendered":"Compiler-Assisted Hybrid Operand Communication"},"content":{"rendered":"<p>Communication of operands among in-flight instructions can be<br \/>\npower intensive, especially in superscalar processors where all result<br \/>\ntags are broadcast to a small number of consumers through a<br \/>\nmulti-entry CAM. Token-based point-to-point communication of<br \/>\noperands in dataflow architectures is highly efficient when each<br \/>\nproduced token has only one consumer, but inefficient when there<br \/>\nare many consumers due to the construction of software fanout<br \/>\ntrees. Placing operands in registers is efficient for broadcasting the<br \/>\nvalues which have consumers spread over a long lifetime, but inefficient<br \/>\nfor shorter-lived operations. This paper evaluates a compilerassisted<br \/>\nhybrid instruction communication model that combine tokens<br \/>\ninstruction communication with statically assigned broadcast<br \/>\ntags. Each fixed-size block of code is given a small number of<br \/>\narchitectural broadcast identifiers, which the compiler can assign<br \/>\nto producers that have many consumers. Producers with few consumers<br \/>\nrely on point-to-point communication through tokens. Producers<br \/>\nwhose result is live past the instruction block communicate<br \/>\nwith distant consumers through a register. Selecting the mechanism<br \/>\nstatically by the compiler relieves the hardware from categorizing<br \/>\ninstructions at runtime. At the same time, a compiler can categorize<br \/>\ninstructions better than dynamic selection does because the<br \/>\ncompiler analyzes a larger range of instructions. Furthermore, compiler<br \/>\ncould perform complex optimizations without hardware cost<br \/>\nand execution-time penalty. We propose a compiler optimization to<br \/>\nreuse broadcast tags for instructions with non-overlapping broadcast<br \/>\nlive ranges, the speedup is further improved without spending<br \/>\nmore power . The results show that this compiler-assisted hybrid<br \/>\ntoken\/broadcast model requires only eight architectural broadcasts<br \/>\nper block, enabling highly efficient CAMs. This hybrid model reduces<br \/>\ninstruction communication energy by 28% compared to a<br \/>\nstrictly token-based dataflow model (and by over 2.7X compared<br \/>\nto a hybrid model without compiler support), while simultaneously<br \/>\nincreasing performance by 8% on average across the SPECINT and<br \/>\nEEMBC benchmarks, running as single threads on 16 composed,<br \/>\ndual-issue EDGE cores.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Communication of operands among in-flight instructions can be power intensive, especially in superscalar processors where all result tags are broadcast to a small number of consumers through a multi-entry CAM. Token-based point-to-point communication of operands in dataflow architectures is highly efficient when each produced token has only one consumer, but inefficient when there are many [&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":"UT-Austin, Department of Computer Science","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"TR-09-33","msr_organization":"","msr_pages_string":"","msr_page_range_start":"","msr_page_range_end":"","msr_series":"","msr_volume":"","msr_copyright":"","msr_conference_name":"","msr_doi":"","msr_arxiv_id":"","msr_s2_paper_id":"","msr_mag_id":"","msr_pubmed_id":"","msr_other_authors":"Dong Li, Madhu Saravana Sibi 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