Exploring Approximate Communication Using Lossy Bitwise Compression on Interconnection Networks

The use of approximate communication has emerged as a promising approach for enhancing the efficiency of communication in parallel computer systems. By sending incomplete or imprecise messages, approximate communication can significantly reduce communication time. In this study, we examine applicati...

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Published in:IEEE access Vol. 11; p. 1
Main Author: Hu, Yao
Format: Journal Article
Language:English
Published: Piscataway IEEE 01.01.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
approximate communication
Communication
Compression algorithms
Data compression
Data models
Error correction
Fault tolerance
Floating point arithmetic
Image coding
Interconnection network
lossy compression
message passing interface (MPI)
Multiprocessor interconnection
Parallel computers
parallel computing
Parallel programming
Prediction algorithms
Predictive models
ISSN:2169-3536, 2169-3536
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Abstract The use of approximate communication has emerged as a promising approach for enhancing the efficiency of communication in parallel computer systems. By sending incomplete or imprecise messages, approximate communication can significantly reduce communication time. In this study, we examine application-level techniques for approximate communication to enable high portability on high-performance interconnection networks. Specifically, we focus on lossy compression of floating-point data, which is frequently exchanged between compute nodes in parallel applications. Our approach involves a simple application scenario where a source process compresses a communication dataset and a destination process decompresses it in an MPI parallel program. We use two bitwise procedures for compression: lossy bit-zip compression and lossless bit-mask compression. Our aim is to transmit the largest possible amount of approximate data with the least possible compression overhead. Additionally, we explore error check and correction techniques to ensure bit-flip fault tolerance for the compressed data during transmission. We implement our scheme in several communication-intensive MPI applications and demonstrate that our approximate communication approach effectively speeds up total execution time while staying within a specified quality-of-result error bound .
AbstractList The use of approximate communication has emerged as a promising approach for enhancing the efficiency of communication in parallel computer systems. By sending incomplete or imprecise messages, approximate communication can significantly reduce communication time. In this study, we examine application-level techniques for approximate communication to enable high portability on high-performance interconnection networks. Specifically, we focus on lossy compression of floating-point data, which is frequently exchanged between compute nodes in parallel applications. Our approach involves a simple application scenario where a source process compresses a communication dataset and a destination process decompresses it in an MPI parallel program. We use two bitwise procedures for compression: lossy bit-zip compression and lossless bit-mask compression. Our aim is to transmit the largest possible amount of approximate data with the least possible compression overhead. Additionally, we explore error check and correction techniques to ensure bit-flip fault tolerance for the compressed data during transmission. We implement our scheme in several communication-intensive MPI applications and demonstrate that our approximate communication approach effectively speeds up total execution time while staying within a specified quality-of-result error bound.
Author Hu, Yao
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SubjectTerms approximate communication
Communication
Compression algorithms
Data compression
Data models
Error correction
Fault tolerance
Floating point arithmetic
Image coding
Interconnection network
lossy compression
message passing interface (MPI)
Multiprocessor interconnection
Parallel computers
parallel computing
Parallel programming
Prediction algorithms
Predictive models
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Title Exploring Approximate Communication Using Lossy Bitwise Compression on Interconnection Networks
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