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IOPA: I/O-aware parallelism adaption for parallel programs.

Tao Liu¹, Yi Liu^1,2, Chen Qian¹

¹Sino-German Joint Software Institute, Beihang University, Beijing, China.

|March 10, 2017

Summary

This summary is machine-generated.

This study introduces IOPA, a mechanism that dynamically adjusts application parallelism to optimize I/O performance. IOPA improves efficiency by balancing system I/O capabilities with application demands, outperforming fixed thread counts.

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Area of Science:

Computer Science
Parallel Computing
Systems Engineering

Background:

Modern multi-/many-core processors require parallel programming for efficiency.
I/O subsystems are critical bottlenecks for data-intensive parallel applications.
Optimizing thread count is crucial for balancing resource utilization and I/O performance.

Purpose of the Study:

To propose a dynamic parallelism control mechanism for I/O-intensive applications.
To develop an interface simplifying parallel programming for I/O optimization.
To adapt application parallelism to underlying system I/O capabilities.

Main Methods:

Developed the IOPA (Intelligent Optimized Parallelism Adjuster) mechanism.
Designed a programming interface for IOPA integration.
Evaluated IOPA with diverse applications on solid-state and hard-disk drives.

Main Results:

IOPA dynamically adjusts application thread parallelism.
The mechanism effectively balances computing resources and I/O bandwidth.
Applications utilizing IOPA demonstrated superior efficiency compared to fixed parallelism.

Conclusions:

IOPA offers an adaptive solution for managing I/O parallelism in multi-core systems.
Dynamic parallelism control enhances application performance and resource utilization.
IOPA simplifies parallel programming while improving execution efficiency.