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Distributed Parity Cache Table

Distributed Parity Cache Table. Motivation. Parity updating is a high cost operation Especially for small write operations Read old data 、 Read Old Parity 、 write new data 、 write new parity Basic ideas Delay the generation of parity Cached data could be used without reread

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Distributed Parity Cache Table

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  1. Distributed Parity Cache Table

  2. Motivation • Parity updating is a high cost operation • Especially for small write operations • Read old data、Read Old Parity、write new data、write new parity • Basic ideas • Delay the generation of parity • Cached data could be used without reread • Parity & newly written data could be cached for “the same” write • Beyond parity? • A server-side cooperative cache

  3. Distributed Parity Cache Table • A whole stripe is more meaningful than partial blocks • Local file system cache knows nothing about a whole stripe • Distributed parity cache table knows !! • Small write phenomenon • Could aggregate small writes • Benefits from previous read • Cooperative cache • PVFS does not provide cache

  4. Architecture

  5. Striping Size and Cache Blocks

  6. Cache Block • Each block contains 16K data + 256 bytes metadata • DTag : Data tag • PTag : Parity tag • LRef : # of hits in this block • GRef: # of hits in this stripe

  7. Cache Replacement Algorithm IF PTag is null THEN IF Operation is READ THEN USE LRef Field & LRU ELSE IF Dirty bit is Set THEN Write the Parity Block and the replaced Block END IF Write Operation Proceed Update the PTag Field END IF ELSE IF PTag == itself.DTag and DTag != itself.DTag THEN Replace the block ELSE IF PTag != DTag USE LRef Field & LRU END IF END IF

  8. Performance Evaluation (1/4) –Native Calls

  9. Performance Evaluation (2/4) –Native Calls

  10. Performance Evaluation (3/4) –POSIX APIs

  11. Performance Evaluation (4/4) – POSIX APIs

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