Semantics-Oriented Low Power Architecture
Innovations in the microarchitecture and prominent advances in the semiconductor process technology enable sophisticated and powerful microprocessors. However, they also lead to increased power consumption. The main contribution of the thesis is the demonstration of Semantics-Oriented Low Power Architecture techniques that use the semantics of memory references and variables used in an application program to reduce the power consumption in the memory sub-system of a microprocessor. The Semantic-Aware Multilateral Partitioning (SAM) technique reduces the cache and TLB power consumption by decoupling the data TLB lookups and the data cache accesses, based on the semantic regions defined by the programming languages and the software convention, into discrete reference sub-streams, namely, stack, global static, and heap. To reduce the power consumed by the snoops in Chip Multiprocessor, we propose a hardware technique called Selective Snoop Probe (SSP) and a compiler-based hardware supported technique called Essential Snoop Probe (ESP) that use the properties of the program variables. By selectively sending the snoop probes, the SSP and ESP techniques relax the conservative nature of the cache coherency protocol and its implementation to reduce power and improve performance.
Advisor:Hsien-Hsin Sean Lee; Abhijit Chatterjee; Bernard Kippelen; Gabriel H. Loh; SungKyu Lim
School:Georgia Institute of Technology
School Location:USA - Georgia
Source Type:Master's Thesis
Keywords:electrical and computer engineering
Date of Publication:04/01/2008