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Exploring efficient architecture design for thread-level speculation---Power and performance perspectives

Posted on:2010-08-02Degree:Ph.DType:Dissertation
University:University of MinnesotaCandidate:Packirisamy, VenkatesanFull Text:PDF
GTID:1448390002979582Subject:Engineering
Abstract/Summary:
With the advent of multi-threaded (e.g. simultaneous multi-threading (SMT) [1, 2]) and/or multi-core (e.g. chip multiprocessors (CMP) [3, 4]) architectures, now the challenge is to utilize these architectures to improve performance of general-purpose applications. However, traditional parallelizing compilers often fail to effectively parallelize general-purpose applications which typically have complex control flow and excessive pointer usage. Thread-Level Speculation (TLS) have been proposed to simplify the task of parallelization by using speculative threads. Though the performance of TLS has been studied in the past, its power consumption, power efficiency and thermal behavior are not well understood. Also previous work on TLS have concentrated on multi-core based architectures and relatively little has been done on supporting TLS on multi-threaded architectures. With increasing multi-threaded/multi-core design choices, it is important to understand the benefits of the different types of architectures.;The goal of this dissertation is to explore architecture techniques to efficiently implement TLS in future multi-threaded/multi-core processors. The dissertation proposes a novel cache-based architecture to support TLS in multi-threaded SMT architecture. A detailed study on the efficiency of different TLS architectures was conducted by comparing their performance, power and thermal characteristics. To improve efficiency, the dissertation proposes a novel SMT-CMP based heterogeneous architecture which combines the advantages of both SMT and CMP architectures. The dissertation also proposes novel architecture and compiler techniques to efficiently extract speculative parallelism from multiple loop levels.
Keywords/Search Tags:Architecture, TLS, Performance, SMT, Power, Dissertation
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