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Execution Replay for Multiprocessor Virtual Machines George W. Dunlap Dominic Lucchetti Michael A. Fetterman Peter M. Chen
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Big ideas Detection and replay of memory races is possible on commodity hardware Overhead high for some workloads …but surprisingly low for other workloads
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Execution Replay CPU Memory Disk Network Keyboard, mouse Interrupts
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Uses of Execution Replay Reconstructing state –Fault tolerance Reconstructing execution –Debugging –Realistic trace generation Both –Intrusion analysis
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Single-processor Replay Basic principles well understood –Log all non-deterministic inputs –Timing of asynchronous events Minimal overhead (Dunlap02) –13% worst case –Log for months or years Available commercially –VMWare: Record/Replay
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Replay for Multiprocessors Memory races in multiprocessor VMs The Ordering Requirement The CREW Protocol –Implementing with page protections –Relation to the Ordering Requirement –Generating constrants from CREW events DMA-capable devices and CREW Performance
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The Multiprocessor Challenge Interleaved reads and writes –Fine-grained non-determinism –Much more difficult Existing solutions –Hardware modification –Software instrumentation SMP-ReVirt –Hardware MMU to detect sharing
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Multiprocessor Replay P2 Memory P1 P2 n=3 n=5 if (n<4)
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Ordering Memory Accesses Preserving order will reproduce execution –a→b: “a happens-before b” –Ordering is transitive: a→b, b→c means a→c Two instructions must be ordered if: –they both access the same memory, and –one of them is a write
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Constraints: Enforcing order To guarantee a→d: –a→d–a→d –b→d–b→d –a→c–a→c –b→c–b→c Suppose we need b→c –b→c is necessary –a→d is redundant P1 a b c d P2 overconstrained
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CREW Protocol Each shared object in one of two states: –Concurrent-Read: all processors can read, none can write –Exclusive-Write: one processor (the owner) can read and write; others have no access
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CREW protocol, con’t Enforced with hardware MMU –Read/write –Read-only –None Change CREW states on demand –Fault, fixup, re-execute CREW event –Increasing or reducing permission due to CREW state changes
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CREW Property If two instructions on different processors: –access the same page, –and one of them is a write, –there will be a CREW event on each processor between them.
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Generating Constraints State: Concurrent Read –All processors read-only d*: CREW fault New state: P2 Exclusive r: privilege reduction –Read to None i: privilege increase –Read to Read/write Log timing of r and i Constraint: –r → i P1 a d P2 r i d*
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Direct Memory Access Device accesses memory directly Logically another processor –Reads and writes need to be ordered –IOMMU: can’t fault/fixup/re-execute Observation: Transaction model Device: non-preemptible actor
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Prototype: SMP-ReVirt Modified Xen hypervisor Implement logging, CREW protocol Details in paper
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Evaluation questions What is the overhead? What affects performance? –In paper When might I want to use MP? –Log with 1, 2, or N cpus?
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Evaluation Workloads SPLASH2 parallel application suite –FMM, LU, ocean, radix, water-spatial, radiosity Kernel-build Dbench
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Predicting results Key changes in sharing attributes –4096-byte sharing granularity –“Miss” is very expensive SPLASH2 –Good: high spatial locality / low false sharing –Bad: random access patterns / high false sharing The Linux kernel –Tuned to 16-byte cacheline –Involving the kernel may be expensive
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Single-processor Xen guests
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Log Growth Rate WorkloadLog growth(GB/day)Days to fill 300GB FMM0.2341280 LU0.2371261 Ocean0.2321295 Radix0.2921025 Water-spatial0.2321296 Kernel-build0.564531 Radiosity0.2311295 Dbench0.557538
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2-processor Xen guests
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2-processor, con’t
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Log Growth Rate WorkloadLog growth(GB/day)Days to fill 300GB FMM34.58.7 LU3.292.7 Ocean4.369.1 Radix39.87.5 Water-spatial36.38.25 Kernel-build43.36.9 Radiosity88.43.4 Dbench77.03.9
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4-processor Xen guests
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Recap Memory races in multiprocessor VMs The Ordering Requirement The CREW Protocol –Implementing with page protections –Relation to the Ordering Requirement –Generating constrants from CREW events DMA-capable devices and CREW Performance
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Big ideas Detection and replay of memory races is possible on commodity hardware Overhead high for some workloads …but surprisingly low for other workloads
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Questions
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