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12/20/2010 1 REMEM: REmote MEMory as Checkpointing Storage Hui Jin Illinois Institute of Technology Xian-He Sun Illinois Institute of Technology Yong Chen Oak Ridge National Laboratory Tao Ke Illinois Institute of Technology CloudCom 2010

REMEM: REmote MEMory as Checkpointing Storagesalsahpc.indiana.edu/CloudCom2010/slides/PDF/REMEM... · It is feasible to implement memory based checkpointing seamlessly. Remote memory

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Page 1: REMEM: REmote MEMory as Checkpointing Storagesalsahpc.indiana.edu/CloudCom2010/slides/PDF/REMEM... · It is feasible to implement memory based checkpointing seamlessly. Remote memory

12/20/2010 1

REMEM: REmote MEMory as Checkpointing Storage

Hui Jin Illinois Institute of TechnologyXian-He Sun Illinois Institute of TechnologyYong Chen Oak Ridge National LaboratoryTao Ke Illinois Institute of Technology

CloudCom 2010

Page 2: REMEM: REmote MEMory as Checkpointing Storagesalsahpc.indiana.edu/CloudCom2010/slides/PDF/REMEM... · It is feasible to implement memory based checkpointing seamlessly. Remote memory

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OutlineBackground & MotivationREMEM DesignImplementation of REMEM on Open MPIAdaptive Checkpointing Storage SelectionExperimental ResultsConclusions & Future Work

CloudCom 2010

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Motivation

Checkpointing is a mostly used mechanism to support fault tolerance in High-Performance Computing environment. However, it introduces considerable overhead due to the expensive

I/O access cost. For a 1-petaFLOPS system, checkpointing can potentially harm the

system performance by 50%.[R. Oldfield al, et 2007]The upcoming Exascale computing environment puts forward even more challenges. 10^18 FLOPS computing power. Millions of computing components. Checkpointing on the centralized parallel file system is not scalable. What if the MTBF < checkpointing cost?

CloudCom 2010

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A detailed look of Checkpointing Cost

J. Hursey, al et, "Interconnect Agnostic Checkpoint/Resart in Open MPI", HPDC 2009

CloudCom 2010

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Motivation

Memory-based checkpointing is a promising solution to break through the bottleneck from the stable storage. But …Rarely supported by the mainstream of current checkpoint systems. Complexity. Reliability Concern. Excess Memory Usage

CloudCom 2010

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REMEM

REmote MEMory as Checkpiting Storage. Seamless integration with existing checkpointing

sysems. Flexible switch between disk and remote memory

as checkpointing storage. Consideration of reliability and space efficiency.

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REMEM – Design Goals

Reliability: Memory is volatile.Scalability: Large-scale environment.Space Efficiency: Memory is precious.Transparency: Augment to existing systems.Flexibility: Switch between the disk and memory.

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REMEM Design

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REMEM – Node Matching

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kn

CC

11 1

k kn k n k

kn

C CC

−− + − −−Reliability:

Z. Chen, etc, Fault Tolerant High Performacne Computing by a Coding Approach, PPoPP’05

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REMEM – System Configuration

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REMEM: Failure Handling

If failures occurs to the source node. If backup node is healthy, simply recovery from

remote memory. If backup node also fails, loads the image from

last disk-based checkpointing.

12/20/2010 CloudCom 2010 11

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REMEM: Implementation on Open MPI

Open source MPI-2 implementation that provides a high performance, robust, parallel execution environment for a wide variety of computing environmentsSupports transparent, coordinated checkpoint/restart implementation supported primarily by the BLCR library.

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REMEM: Implementation on Open MPI

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Adaptive Checkpionting Storage SelectionDisk:Memory:

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Experimental Setup

Hardware A 65-node SunFire Cluster. Compute Nodes.

Dual 2.3GHz Opteron quad-core processors and 8GB memory, 250GB 7.2K-RPM SATA hard drive.

OS: Ubuntu enterprise server with Linux kernel 2.6.10

Software: Open MPI v1.3.3 and GCC 4.3.3 REMEM was implemented on the Open MPI with the support of tmpfs

and NFS 3.0.

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Experimental Setup

The 64 compute nodes are organized in two groups naturally by the rack id. The nodes from the two groups are mutually mapped for REMEM.4 dedicated X2200 computer nodes configured as PVFS2 servers. Results were obtained for the NAS Parallel Benchmarks (NPB) version 3.3.

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REMEM Performance

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Problem Size Scaling Performance

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Task Scaling Performance

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Adaptive Checkpointing Storage Selection

Simulate a cluster of 2048 nodes.For each node, we generate a series of failure arrivals withWeibull distribution. MTBF = 7668 Hours; shape parameter = 0.7

12/20/2010 CloudCom 2010 20

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Adaptive Checkpointing Storage Selection -Metrics

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Rework Cost

Restart Cost Useful Work

Checkpoint

Page 22: REMEM: REmote MEMory as Checkpointing Storagesalsahpc.indiana.edu/CloudCom2010/slides/PDF/REMEM... · It is feasible to implement memory based checkpointing seamlessly. Remote memory

Adaptive Checkpointing Storage Selection

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Performance with Different Number of Processes

Page 23: REMEM: REmote MEMory as Checkpointing Storagesalsahpc.indiana.edu/CloudCom2010/slides/PDF/REMEM... · It is feasible to implement memory based checkpointing seamlessly. Remote memory

Adaptive Checkpointing Storage Selection

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Performance with Different Number of I/O Nodes

Page 24: REMEM: REmote MEMory as Checkpointing Storagesalsahpc.indiana.edu/CloudCom2010/slides/PDF/REMEM... · It is feasible to implement memory based checkpointing seamlessly. Remote memory

Adaptive Checkpointing Storage Selection

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Performance with Different Checkpointing Interval

Page 25: REMEM: REmote MEMory as Checkpointing Storagesalsahpc.indiana.edu/CloudCom2010/slides/PDF/REMEM... · It is feasible to implement memory based checkpointing seamlessly. Remote memory

Future Work

Release the software.More flexible node matching.How the HPC checkpointing looks like in the cloud?Adopt MapReduce as Checkponiting storage?

12/20/2010 CloudCom 2010 25

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Conclusions

It is feasible to implement memory based checkpointing seamlessly.Remote memory is a promising alternative to existing disk as checkpointing storage.Memory should be used in combination with disk to guarantee reliability while achieving efficiency.

12/20/2010 CloudCom 2010 26

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Thanks!Questions?http://www.cs.iit.edu/~scs

12/20/2010 27CloudCom 2010