GPU Execution Tracing and Compression

Program tracing is widely used for debugging and performance optimization. Whenever a program is traced, the overhead in terms of extra runtime and in terms of storage for the generated trace information are a concern. These concerns are greatly exacerbated on GPUs due to the large amount of parallelism. In fact, GPUs provide such massive parallelism that conventional tracing approaches either fail or only manage to trace very few events per thread. Hence, we need not only a low-overhead but also a space-efficient approach to make detailed tracing possible on GPUs. To the best of my knowledge, none of the existing GPU tracing tools support both. Thus, in this thesis, I developed an execution tracing tool for GPUs called ECL-Tracer that is light-weight and immediately compresses the generated trace data before they are stored.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

Masters

Discipline thesis:degree_discipline

Computer Science

Grantor

Texas State University

Year dc:date.issued

2017

Author dc:creator

• Azimi Moghaddam, Sahar

Advisor dc:contributor.advisor

• Burtscher, Martin

Committee members dc:contributor.committeemember

• Qasem, Apan
• Zong, Ziliang

• GPU execution tracing
• GPU trace compression
• trace compression
• parallel programming
• data compression

Language dc:language.iso

en

Handle dc:identifier.uri

https://hdl.handle.net/10877/7738

OAI identifier oai:identifier

oai:digital.library.txst.edu:10877/7738