| Author | Govindan, Madhu Sarava |
| Title | E³ : energy-efficient EDGE architectures |
| URL | http://hdl.handle.net/2152/ETD-UT-2010-08-1934  |
| Publication Date | 2010 |
| Date Accessioned | 2010-12-13 20:31:31 |
| Degree | PhD |
| Discipline/Department | Computer Sciences |
| Degree Level | doctoral |
| University/Publisher | University of Texas – Austin |
| Abstract | Increasing power dissipation is one of the most serious challenges facing designers in the microprocessor industry. Power dissipation, increasing wire delays, and increasing design complexity have forced industry to embrace multi-core architectures or chip multiprocessors (CMPs). While CMPs mitigate wire delays and design complexity, they do not directly address single-threaded performance. Additionally, programs must be parallelized, either manually or automatically, to fully exploit the performance of CMPs. Researchers have recently proposed an architecture called Explicit Data Graph Execution (EDGE) as an alternative to conventional CMPs. EDGE architectures are designed to be technology-scalable and to provide good single-threaded performance as well as exploit other types of parallelism including data-level and thread-level parallelism. In this dissertation, we examine the energy efficiency of a specific EDGE architecture called TRIPS Instruction Set Architecture (ISA) and two microarchitectures called TRIPS and TFlex that implement the TRIPS ISA. TRIPS microarchitecture is a first-generation design that proves the feasibility of the TRIPS ISA and distributed tiled microarchitectures. The second-generation TFlex microarchitecture addresses key inefficiencies of the TRIPS microarchitecture by matching the resource needs of applications to a composable hardware substrate. First, we perform a thorough power analysis of the TRIPS microarchitecture. We describe how we develop architectural power models for TRIPS. We then improve power-modeling accuracy using hardware power measurements on the TRIPS prototype combined with detailed Register Transfer Level (RTL) power models from the TRIPS design. Using these refined architectural power models and normalized power modeling methodologies, we perform a detailed performance and power comparison of the TRIPS microarchitecture with two different processors: 1) a low-end processor designed for power efficiency (ARM/XScale) and 2) a high-end superscalar processor designed for high performance (a variant of Power4). This detailed power analysis provides key insights into the advantages and disadvantages of the TRIPS ISA and microarchitecture compared to processors on either end of the performance-power spectrum. Our results indicate that the TRIPS microarchitecture achieves 11.7 times better energy efficiency compared to ARM, and approximately 12% better energy efficiency than Power4, in terms of the Energy-Delay-Squared (ED²) metric. Second, we evaluate the energy efficiency of the TFlex microarchitecture in comparison to TRIPS, ARM, and Power4. TFlex belongs to a class of microarchitectures called Composable Lightweight Processors (CLPs). CLPs are distributed microarchitectures designed with simple cores and are highly configurable at runtime to adapt to resource needs of applications. We develop power models for the TFlex microarchitecture based on the validated TRIPS power models. Our quantitative results indicate that by better matching execution resources to the needs of… |
| Subjects/Keywords | Energy efficiency; EDGE architectures; Power efficiency; Composability; DVFS; Power management; Dynamic voltage and frequency scaling; Explicit Data Graph Execution architectures |
| Contributors | Keckler, Stephen W. (advisor); Burger, Douglas C. (committee member); McKinley, Kathryn S. (committee member); Chiou, Derek (committee member); Hunt, Jr., Warren A. (committee member); Brooks, David (committee member) |
| Language | en |
| Country of Publication | us |
| Record ID | handle:2152/ETD-UT-2010-08-1934 |
| Repository | texas |
| Date Indexed | 2020-10-15 |
| Grantor | University of Texas at Austin |
| Note | [] text; [department] Computer Sciences; |
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