Scalable Cosmological Simulations on Parallel Machines

Gioachin, Filippo; Sharma, Amit; Chakravorty, Sayantan; Mendes, Celso L.; Kalé, Laxmikant V.; Quinn, Thomas R.

doi:10.1007/978-3-540-71351-7_37

Cited by 11 publications

(12 citation statements)

References 8 publications

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“…The first one is wave2D, which uses a finite differencing scheme to calculate pressure information over a discretized 2D grid. The second application, ChaNGa, is for N-Body based parallel simulations and is used in cosmology and astronomy [12].…”

Section: Experiments and Analysismentioning

confidence: 99%

Hiding Checkpoint Overhead in HPC Applications with a Semi-Blocking Algorithm

Meneses

Kalé

2012

2012 IEEE International Conference on Cluster Computing

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Abstract-The HPC community has seen a steady increase in the number of components in every generation of supercomputers. Assembling a large number of components into a single cluster makes a machine more powerful, but also much more prone to failures. Therefore, fault tolerance has become a major concern in HPC. To deal with node crashes in large systems, checkpoint/restart is by far the preferred method. A typical way to implement checkpoints is by using a blocking algorithm, which suspends the execution of the application while the checkpoint is safely stored. One limitation of the blocking algorithm is that it saturates the network bandwidth at the time of checkpoint. This problem will become even more critical because the projected network bandwidth increase will not match the increase in memory per node. To alleviate this problem, we have developed a semi-blocking checkpoint algorithm that overlaps execution of the application with transmission of checkpoints. Our implementation decomposes a checkpoint into small messages that are interleaved with application messages. The experimental results show a dramatic reduction in the checkpoint overhead for various applications. We present a model for our approach and use this model to compute the benefit of the semi-blocking algorithm for different failure rates predicted at Exascale. We estimate our method can reduce up to 22% the total execution time of an iterative scientific application.

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Section: Experiments and Analysismentioning

confidence: 99%

Hiding Checkpoint Overhead in HPC Applications with a Semi-Blocking Algorithm

Meneses

Kalé

2012

2012 IEEE International Conference on Cluster Computing

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“…For each application, less than 0.5% of the application code was affected. ChaNGa [19], [20] is a code for performing collisionless N-body simulations. It simulates cosmological phenomena with periodic boundary conditions in comoving coordinates or isolated stellar systems.…”

Section: Application Resultsmentioning

confidence: 99%

TRAM: Optimizing Fine-Grained Communication with Topological Routing and Aggregation of Messages

Wesolowski

Venkataraman

Gupta

et al. 2014

2014 43rd International Conference on Parallel Processing

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Abstract-Fine-grained communication in supercomputing applications often limits performance through high communication overhead and poor utilization of network bandwidth. This paper presents Topological Routing and Aggregation Module (TRAM), a library that optimizes fine-grained communication performance by routing and dynamically combining short messages. TRAM collects units of fine-grained communication from the application and combines them into aggregated messages with a common intermediate destination. It routes these messages along a virtual mesh topology mapped onto the physical topology of the network. TRAM improves network bandwidth utilization and reduces communication overhead. It is particularly effective in optimizing patterns with global communication and large message counts, such as all-to-all and many-to-many, as well as sparse, irregular, dynamic or data dependent patterns. We demonstrate how TRAM improves performance through theoretical analysis and experimental verification using benchmarks and scientific applications. We present speedups on petascale systems of 6x for communication benchmarks and up to 4x for applications.

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“…Processor virtualization also enables runtime measurement based dynamic load balancing. The idea has been useful in numerous applications from molecular dynamics [21] to cosmology [14]. AMPI is an implementation of MPI on top of the Charm++ runtime system that allows traditional MPI codes to reap the benefits of virtualization such as latency tolerance and runtime load balancing.…”

Section: Related Workmentioning

confidence: 99%

A Fault Tolerance Protocol with Fast Fault Recovery

Chakravorty

Kalé

2007

2007 IEEE International Parallel and Distributed Processing Symposium

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Fault tolerance is an important issue for large machines with tens or hundreds of thousands of processors. Checkpoint-based methods, currently used on most machines, rollback all processors to previous checkpoints after a crash. This wastes a significant amount of computation as all processors have to redo all the computation from that checkpoint onwards. In addition, recovery time is bound by the time between the last checkpoint and the crash. Protocols based on message logging avoid the problem of rolling back all processors to their earlier state. However, the recovery time of existing message logging protocols is no smaller than the time between the last checkpoint and crash. We present a fault tolerance protocol, in this paper, that provides fast restarts by using the ideas of message logging and object-based processor virtualization. We evaluate our implementation of the protocol in the Charm++/Adaptive MPI runtime system. We show that our protocol provides fast restarts and, for many applications, has low fault-free overhead.

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Scalable Cosmological Simulations on Parallel Machines

Cited by 11 publications

References 8 publications

Hiding Checkpoint Overhead in HPC Applications with a Semi-Blocking Algorithm

Hiding Checkpoint Overhead in HPC Applications with a Semi-Blocking Algorithm

TRAM: Optimizing Fine-Grained Communication with Topological Routing and Aggregation of Messages

A Fault Tolerance Protocol with Fast Fault Recovery

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