Paper Info
Title
Energy-Aware Data Allocation With Hybrid Memory for Mobile Cloud Systems
Abstract
Resource scheduling is one of the most important issues in mobile cloud computing due to the constraints in memory, CPU, and bandwidth. High energy consumption and low performance of memory accesses have become overwhelming obstacles for chip multiprocessor (CMP) systems used in cloud systems. In order to address the daunting “memory wall” problem, hybrid on-chip memory architecture has been widely investigated recently. Due to its advantages in size, real-time predictability, power, and software controllability, scratchpad memory (SPM) is a promising technique to replace the hardware cache and bridge the processor–memory gap for CMP systems. In this paper, we present a novel hybrid on-chip SPM that consists of a static random access memory (RAM), a magnetic RAM (MRAM), and a zero-capacitor RAM for CMP systems by fully taking advantages of the benefits of each type of memory. To reduce memory access latency, energy consumption, and the number of write operations to MRAM, we also propose a novel multidimensional dynamic programming data allocation (MDPDA) algorithm to strategically allocate data blocks to each memory. Experimental results show that the proposed MDPDA algorithm can efficiently reduce the memory access cost and extend the lifetime of MRAM.
Year
DOI
Venue
2017
10.1109/JSYST.2014.2345733
IEEE Systems Journal
Keywords
Field
DocType
Chip multiprocessor (CMP),data allocation,hybrid memory,magnetic RAM (MRAM),mobile cloud,scratchpad memory (SPM),zero-capacitor RAM (Z-RAM)
Registered memory,Semiconductor memory,Interleaved memory,Uniform memory access,Computer science,Non-volatile random-access memory,Real-time computing,Memory management,Flat memory model,Computer memory
Journal
Volume
Issue
ISSN
PP
99
1932-8184
Citations 
PageRank 
References 
51
1.39
17
Authors
4
Name
Order
Citations
PageRank
Min Qiu1656.12
Z. Chen243238.14
Zhong Ming31377106.41
Xiao Qin41836125.69