Paper Info
Title
Improving Performance of Iterative Methods by Lossy Checkponting.
Abstract
Iterative methods are commonly used approaches to solve large, sparse linear systems, which are fundamental operations for many modern scientific simulations. When the large-scale iterative methods are running with a large number of ranks in parallel, they have to checkpoint the dynamic variables periodically in case of unavoidable fail-stop errors, requiring fast I/O systems and large storage space. To this end, significantly reducing the checkpointing overhead is critical to improving the overall performance of iterative methods. Our contribution is fourfold. (1) We propose a novel lossy checkpointing scheme that can significantly improve the checkpointing performance of iterative methods by leveraging lossy compressors. (2) We formulate a lossy checkpointing performance model and derive theoretically an upper bound for the extra number of iterations caused by the distortion of data in lossy checkpoints, in order to guarantee the performance improvement under the lossy checkpointing scheme. (3) We analyze the impact of lossy checkpointing (i.e., extra number of iterations caused by lossy checkpointing files) for multiple types of iterative methods. (4) We evaluate the lossy checkpointing scheme with optimal checkpointing intervals on a high-performance computing environment with 2,048 cores, using a well-known scientific computation package PETSc and a state-of-the-art checkpoint/restart toolkit. Experiments show that our optimized lossy checkpointing scheme can significantly reduce the fault tolerance overhead for iterative methods by 23%∼70% compared with traditional checkpointing and 20%∼58% compared with lossless-compressed checkpointing, in the presence of system failures.
Year
DOI
Venue
2018
10.1145/3208040.3208050
HPDC
Keywords
DocType
Volume
Iterative Methods, Numerical Linear Algebra, Resilience, Check-point/Restart, Lossy Compression, Performance Optimization
Conference
abs/1804.11268
ISBN
Citations 
PageRank 
978-1-4503-5785-2
1
0.36
References 
Authors
32
5
Name
Order
Citations
PageRank
Dingwen Tao112917.66
Sheng Di273755.88
Xin Liang310712.74
Zizhong Chen492469.93
Franck Cappello53775251.47