A Study of Energy Efficiency Methods for Memory

A Study of Energy Efficiency A Study of Energy Efficiency Methods for MemoryMethods for Memory

Mao-Yin Wang & Cheng-Wen Wu

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Memory Energy ReductionMemory Energy ReductionMemory Energy ReductionMemory Energy Reduction

Memory Compression

Memory Partitioning

Sleep mode control

Memory bandwidth optimization

Memory Hierarchy

Software ApproachAccess Pattern AnalysisLocality

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OutlineOutlineOutlineOutline

Introduction

Relative works

Conclusions

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Related WorkRelated WorkRelated WorkRelated Work A. Farahi, G. Telez, M. Sarrafzadeh, “Memory Segmentatio

n to Exploit Sleep Mode Operation”, DAC’95, pp. 36-41. L. Benini A. Macii, E. Macii, M. Poncino, “Region Compress

ion: A New Scheme for Memory Energy Minimization in Embedded Systems”, EUROMICRO conference, 1999, pp. 311-317.

L. Benini, A. Macii, E. Macii, M. Poncino, “Minimizing Memory Access Energy in Embedded Systems by Selective Instruction Compression”, IEEE Trans. On VLSI, vol. 10. pp. 521-531, Oct. 2002.

L. Benini, L. Macchiarulo, A. Macii, M. Poncino, “Layout-Driven Memory Synthesis for Embedded Systems-on-Chip”, IEEE Trans. on VLSI, vol. 10, pp. 96-105, Apr. 2002.

A. Macii, E. Macii, M. Poncino, “Improving the Efficiency of Memory Partitioning by Address Clustering”, DATE’03, pp. 18-23.

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Introduction (1/2)Introduction (1/2)Introduction (1/2)Introduction (1/2)

Source: ITRS 2000Source: ITRS 2000

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Introduction (2/2)Introduction (2/2)Introduction (2/2)Introduction (2/2)

According to the ITRS, expected 71% of area is occupied by memory in 2005

Memory is power hungry

Data-intensive applications in embedded systems

Energy efficiency is necessary

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Memory Segmentation [1]Memory Segmentation [1]Memory Segmentation [1]Memory Segmentation [1]

Based on sleep mode

)(),( 212121 swswattssG

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Memory Compression (1/3) [2]Memory Compression (1/3) [2]Memory Compression (1/3) [2]Memory Compression (1/3) [2]

Based on consecutive instruction group in a program

Limited by # of instructions in a compression region

Based on consecutive instruction group in a program

Limited by # of instructions in a compression region

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Memory Compression (2/3)Memory Compression (2/3)Memory Compression (2/3)Memory Compression (2/3)

(1)(1)

(2)(2)

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Memory Compression (3/3)Memory Compression (3/3)Memory Compression (3/3)Memory Compression (3/3)

(3.1)(3.1)(3.2)(3.2)

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Instruction Fetch Energy for Off-Chip Instruction Fetch Energy for Off-Chip FLASH MemoryFLASH Memory

Instruction Fetch Energy for Off-Chip Instruction Fetch Energy for Off-Chip FLASH MemoryFLASH Memory

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Memory TrafficMemory TrafficMemory TrafficMemory Traffic

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Memory UsageMemory UsageMemory UsageMemory Usage

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Memory Partitioning [4]Memory Partitioning [4]Memory Partitioning [4]Memory Partitioning [4]

CoreCore

SRAM

(64K)

SRAM

(64K)

datadataaddraddr

cs

28K28K

4K4K

32K32K

DecoderDecoder

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Address ClusteringAddress ClusteringAddress ClusteringAddress Clustering

43.5% Energy Reduction43.5% Energy Reduction

56% Energy Reduction56% Energy Reduction

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Problem FormulationProblem FormulationProblem FormulationProblem Formulation

Find a relocation of a subset of the address space that maximizes the locality of the dynamic trace.

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Cost MetricsCost MetricsCost MetricsCost Metrics Given an array C = [c0, c1, …, cN-1] Infer a single-value quantity that express its

degree of spatial locality Find good sliding window such that the

density is large and the sliding window is small (i.e. less encoder overhead)

1

0iS

W-N 0,...,i )(max

W

jji

ii

c

SD(C,W)

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Density of the Original and a Clustered Density of the Original and a Clustered TraceTrace

Density of the Original and a Clustered Density of the Original and a Clustered TraceTrace

Sliding window WSliding window W

Normalized densityNormalized density

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Exploration AlgorithmExploration AlgorithmExploration AlgorithmExploration Algorithm

} 8

step; W7

return W; 6

{ Density)) T,,(C peif(EvalSlo 5

W);,d(C Density 4

{ N) to1 (W for 3

Sort(C);C 2

{ T)Explore(C, 1

sort

sort

sort

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Clustering AlgorithmClustering AlgorithmClustering AlgorithmClustering Algorithm

} 4

addresses visitedremaining Replace 3

mark them and sboth tracein addresses Find 2

{ GoldTrace) W,,(OrigTraceCluster 1

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Energy Savings (1/2)Energy Savings (1/2)Energy Savings (1/2)Energy Savings (1/2)

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Energy Savings (2/2)Energy Savings (2/2)Energy Savings (2/2)Energy Savings (2/2)

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Encoder Energy Overhead vs. MEncoder Energy Overhead vs. MEncoder Energy Overhead vs. MEncoder Energy Overhead vs. M

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ConclusionsConclusionsConclusionsConclusions

Energy efficiency methods are studied

Reduce memory traffic

Partition memory as smaller ones

Disable memory blocks

Trade off between performance and energy

Application-dependent