cache performance evaluation under multi-parameters using smpcache simulator

Jordan University Computer Engineering Department

Computer Performance Evaluation Project

Supervisor: Dr. Ghieth AbandahStudent: Aieshah F. Almaslam

1

Outline Introduction Simulator Workload Metrics Design alternatives Implementation Results Analysis Conclusion & Future work

2

3

Why cache ?

High cache performance leads to high total system performance

Cache performance parameters

Cache size Cache block size Cache levels Cache mapping Replacement policy Unified cache or splittedVery big range of combinations, so we need to

parameter performance evaluation.

4

Outline Introduction Simulator Workload Metrics Design alternatives Implementation Results Analysis Conclusion & Future work

5

6

SMPCache simulator Trace driven simulatorWindows compatibleUser friendly interfaceWide range of configurationUniprocessor build in memory tracesMultiprocessor downloaded memory tracesCreating your own memory tracesText and graph results

Simulator

SMPCache User-friendly interface

7

8

Organization of memory SMP or DSM

Number of processors 1, 2, 4, 8, 16, 32, 64 or 128

Snoopy Protocol MSI, MESI or DRAGON

Bus arbitration random, LFU or LRU

Directory protocol SGI or offWord Width (bits( 8, 16, 32 or 64Words in a block 1, 2, 4, 8, 16, 32, 64, 128, up to 1024

Memory Blocks 1, 2, 4, 8, 16, 32, 64, up to 4194304.

Cache Levels 1, 2, 3 or 4Unified or splitted unified or data and instructions

Cache Blocks 1, 2, 4, 8, 16, 32, 64, 128, 256, 512, 1024 or 2048

Mapping Direct, set-associative or fully associative

Cache sets in case of set-associative mapping

Replacement policy Random, LRU, LFU or FIFOWriting strategy Writeback

Architectural characteristics supported by SMPCache

Outline Introduction SMPCache Simulator Workload Metrics Design alternatives Implementation Results Analysis Conclusion & Future work

9

10

Memory traces from SPEC’92 Benchmarks

Uni-processor tracesReal applicationsBuild in simulator softwareDifferent types of applicationsInteger and floating pointExamples: Hydro, Nasa7, Cexp, Mdljd, Ear,

Comp, Wave, Swm and UComp

Workload

Outline Introduction SMPCache Simulator Workload Metrics Design alternatives Implementation Results Analysis Conclusion & Future work

11

12

Miss rate

Less miss rate less main memory access indication on execution delay less ink in the final graph

Metric performance

Outline Introduction SMPCache Simulator Workload Metrics Design alternatives Implementation Results Analysis Conclusion & Future work

13

14

Design alternatives for Cache size factor

Main memory size 64 Gbytes

Block size 16 Kbytes

Cache mapping fully associative

cache replacement Policy LRU

Cache levels 1

Cache levels size 16 / 32 / 64 / 128 / 256 / 1000 Kbytes

Memory traces Comp/Nasa7/hydro

15

Design alternatives

for Cache multi-level factor

Main memory size 64 Gbytes

Block size 16 Kbytes

cache mapping fully associative

cache replacement Policy LRU

Cache levels 1/2/3/4

Cache levels size 16 / 32 / 64 / 128 Kbytes in order

Memory traces Comp/Nasa7/hydro

16 / 32 / 64 / 128 Kbytes

16

Design alternatives

for Cache maping factor

Main memory size 64 Gbytes

Block size 16 Kbytes

cache mapping direct , 2,4,8,16,32 set associatiev and fully associative

cache replacement Policy LRU

Cache levels 1

Cache levels size 16 Kbytes

Memory traces Comp/Nasa7/hydro

Outline Introduction SMPCache Simulator Workload Metrics Design alternatives Implementation Results Analysis Conclusion & Future work

17

ImplementationIn each simulation experiment

Determine Main memory cache configuration Select the desired option from list menu Run the simulation Record the result

18

Outline Introduction SMPCache Simulator Workload Metrics Design alternatives Implementation Results Analysis Conclusion & Future work

19

An Example of one experiment result

20

Cache Performance whencache size is changed

21

Cache Performance whencache levels is changed

22

Cache Performance when cache mapping is changed

23

Outline Introduction SMPCache Simulator Workload Metrics Design alternatives Implementation Results Analysis Conclusion & Future work

24

25

Higher cache performance Higher cache size Higher cache levels Higher associativity - But there is a ”Tradeoff”

Conclusion

26

Evaluate cache performance by studying More factors

Factor interaction

Future Work

Any Question?

27

Eng. Aiesha F. Al-maslam