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Static and Dynamic Instruction Mapping for Spatial Architectures
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Static and Dynamic Instruction Mapping for Spatial Architectures. |
| 개인저자 | Liu, Feng. |
| 단체저자명 | Princeton University. Electrical Engineering. |
| 발행사항 | [S.l.]: Princeton University., 2018. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
| 형태사항 | 120 p. |
| 기본자료 저록 | Dissertation Abstracts International 79-10B(E). Dissertation Abstract International |
| ISBN | 9780438047402 |
| 학위논문주기 | Thesis (Ph.D.)--Princeton University, 2018. |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B.
Adviser: David August. |
| 요약 | In response to the technology scaling trends, spatial architectures have emerged as a new style of processors for executing programs more efficiently. Unlike traditional Out-of-Order (OoO) processors, which time-share a small set of functional u |
| 요약 | Currently, spatial architectures mainly use static methods to map instructions onto the arrays of functional units. The existing methods have several limitations: First, for programs with irregular memory accesses and control flows, they yield p |
| 요약 | To address these issues and improve the applicability of spatial architectures, this dissertation proposes two techniques. The first, Coarse-Grained Pipelined Accelerators (CGPA), is a static compiling framework that exploits the hidden parallel |
| 요약 | The second technique, Dynamic Spatial Architecture Mapping (DYNASPAM), reuses the speculation system in the OoO processors to dynamically produce high-performance scheduling and execution on a dedicated spatial fabric. The proposed technique is |
| 일반주제명 | Computer engineering. Computer science. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
