new visual characterization graphs for memory system analysis and evaluation edson t. midorikawa...
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![Page 1: New Visual Characterization Graphs for Memory System Analysis and Evaluation Edson T. Midorikawa edson.midorikawa@poli.usp.br Hugo Henrique Cassettari](https://reader035.vdocument.in/reader035/viewer/2022062320/56649d795503460f94a5d6c1/html5/thumbnails/1.jpg)
New Visual Characterization New Visual Characterization Graphs for Memory System Graphs for Memory System
Analysis and EvaluationAnalysis and Evaluation
Edson T. [email protected]
Hugo Henrique [email protected]
LAHPC - PCSEscola Politécnica da USP
WSO 2006
3º Workshop de Sistemas OperacionaisCampo Grande – MS
17/julho/2006
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WSO 2006 2
TopicsTopics
• Introduction
• Previous work
• New Proposed Graphs
• Case study: performance of adaptive page replacement algorithms
• Conclusion and Future works
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WSO 2006 3
IntroductionIntroduction
• Memory systems (still) are one of the most important components of modern computer systems.
• They work based on the Principle of Locality of References.
• Workload characterization is essential for memory management research.
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WSO 2006 4
Previous WorkPrevious Work
• WSO 2004– LRU-WAR (LRU with Working Area Restriction)
• WSO 2005– 3P (Three Pointers)
• Performance comparison among algorithms:– FIFO, LRU, Clock, …– FBR, 2Q, …– SEQ, EELRU, LIRS, ARC, CAR, CART
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WSO 2006 5
A simple questionA simple question
Why algorithm A has better performance than algorithm B
for program Punder condition C?
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WSO 2006 6
Previous WorkPrevious Work
Memory access map
Locality surface
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WSO 2006 7
ObjectiveObjective
• Introduce new visual resources to study memory access behavior, workload characterization, and performance prediction.
• Present a case study with the proposed visual characterization graphs.
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WSO 2006 8
New Proposed GraphsNew Proposed Graphs
• We introduce 6 new visual characterization graphs:
– Memory access surface– IRG graph– IRR graph– IRR surface– IRR histogram– IRR cumulative graph
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WSO 2006 9
Case StudyCase Study
• We present a case study of performance evaluation of page replacement algorithms for modern virtual memory systems– Traditional: FIFO, LRU, FBR, 2Q– Adaptive: ARC, EELRU, LIRS, LRU-WAR– Online: Clock, CAR, CART, 3P
• Applications (trace files):– Compress: file compression utility.– Espresso: a circuit simulator.– Grobner: a formula-rewrite program.– Sprite: from the Sprite network file system.
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WSO 2006 10
Case StudyCase Study
• Simulation results
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WSO 2006 11
Memory access surfaceMemory access surface
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WSO 2006 12
Case StudyCase Study
• Grobner
– It uses almost all pages in the virtual address space.
– High access density:• Sequential access pattern.• Temporal reuse of low address pages.
– Good results for page replacement algorithms that detect sequential patterns.
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WSO 2006 13
DefinitionsDefinitions
• IRG (inter-reference gap)– Time distance between successive references of a
memory page.
• IRR (inter-reference recency)– reuse distance or recency– number of other unique pages accessed between two
consecutive references to the same memory page.
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WSO 2006 14
IRG GraphIRG Graph
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WSO 2006 15
IRR GraphIRR Graph
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WSO 2006 16
IRR SurfaceIRR Surface
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WSO 2006 17
Case StudyCase Study
• Sprite
– IRG graph: most of accesses occur in virtual time intervals between 1 and 5,000 references.
– IRR graph + IRR surface: most accesses occur in the first 1,000 positions in the LRU stack (15% of the footprint).
– It presents pages with strong temporal locality being alternating with less accessed pages:
• Not favorable to adaptive algorithms.
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WSO 2006 18
IRR HistogramsIRR Histograms
IRRHistogram
IRRCumulativeHistogram
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WSO 2006 19
Case StudyCase Study
• Compress
– A memory size equal to 8 pages is enough to maintain the page fault rate as low as 18,7%.
– With 64 pages: 1.45%.
– It presents high temporal locality;– It provides more accurate distinction among different
processing phases by adaptive algorithms:• Good performance of adaptive algorithms.
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WSO 2006 20
ConclusionConclusion
• In this paper we introduced six new graphs for studying locality of references.
• Visual aspects:– Memory access patterns;– Temporal and spatial localities;– Real distribution of memory accesses;– Reuse frequency;– LRU stack position.
• The performance of page replacement algorithms was analyzed using these new graphs.
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WSO 2006 21
Future WorkFuture Work
• More case studies– Parallel applications
• New metric: IRR-n (number of distinct pages referenced among n+1 consecutive accesses to the same page).
• Integration and enhancement of the tools available in Elephantools.
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WSO 2006 22
Thank you.
Questions?
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Extra slidesExtra slides
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WSO 2006 24
Locality SurfaceLocality Surface
• Technique to quantify temporal and spatial locality in programs
• Introduced to cache memory studies.• Characterize the memory accesses taking into
account the complete program:– Z-axis: number of occurrences of specific delay (stack
distance) and stride (difference between memory addresses) values obtained among inter-referenced pages
– X-axis: – Y-axis:
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WSO 2006 25
Case StudyCase Study
• Simulation experiments