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Static Instruction Scheduling for High Performance on Limited Hardware
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
National University of Singapore.
Royal Institute of Technology.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems. Norwegian University of Science and Technology.ORCID iD: 0000-0003-4232-6976
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(English)In: IEEE Transactions on ComputersArticle in journal (Refereed) Accepted
Abstract [en]

Complex out-of-order (OoO) processors have been designed to overcome the restrictions of outstanding long-latency misses at the cost of increased energy consumption. Simple, limited OoO processors are a compromise in terms of energy consumption and performance, as they have fewer hardware resources to tolerate the penalties of long-latency loads. In worst case, these loads may stall the processor entirely. We present Clairvoyance, a compiler based technique that generates code able to hide memory latency and better utilize simple OoO processors. By clustering loads found across basic block boundaries, Clairvoyance overlaps the outstanding latencies to increases memory-level parallelism. We show that these simple OoO processors, equipped with the appropriate compiler support, can effectively hide long-latency loads and achieve performance improvements for memory-bound applications. To this end, Clairvoyance tackles (i) statically unknown dependencies, (ii) insufficient independent instructions, and (iii) register pressure. Clairvoyance achieves a geomean execution time improvement of 14% for memory-bound applications, on top of standard O3 optimizations, while maintaining compute-bound applications' high-performance.

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Computer Sciences
Identifiers
URN: urn:nbn:se:uu:diva-334011DOI: 10.1109/TC.2017.2769641OAI: oai:DiVA.org:uu-334011DiVA: diva2:1158485
Projects
UPMARC
Funder
Swedish Research Council, 2016-05086
Available from: 2017-11-20 Created: 2017-11-20 Last updated: 2017-11-22

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Tran, Kim-AnhSjälander, MagnusSpiliopoulos, VasileiosKaxiras, Stefanos

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