Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/11326
Title: Temperature-aware data allocation for embedded systems with cache and scratchpad memory
Authors: Jia, Z
Li, Y
Wang, Y
Wang, M
Shao, Z 
Keywords: Algorithms
Design
Performance
Issue Date: 2015
Publisher: Association for Computing Machinery
Source: ACM transactions on embedded computing systems, 2015, v. 14, no.2, 30 How to cite?
Journal: ACM Transactions on Embedded Computing Systems 
Abstract: The hybrid memory architecture that contains both on-chip cache and scratchpad memory (SPM) has been widely used in embedded systems. In this article, we explore this hybrid memory architecture by jointly optimizing time performance and temperature for embedded systems with loops. Our basic idea is to adaptively adjust the workload distribution between cache and SPM based on the current temperature. For a problem in which the workload can be estimated a priori, we present a nonlinear programming formulation to optimally minimize the total execution time of a loop under the constraints of SPM size and temperature. To solve a problem in which the workload is not known a priori, we propose a temperature-aware adaptive loop scheduling algorithm called TALS to dynamically allocate data to cache and SPM at runtime. The experimental results show that our algorithms can effectively achieve both performance and temperature optimization for embedded systems with cache and SPM.
URI: http://hdl.handle.net/10397/11326
ISSN: 1539-9087
DOI: 10.1145/2629650
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