SC12 Home > SC12 Schedule > SC12 Presentation - Automated Mapping Streaming Applications onto GPUs

SCHEDULE: NOV 10-16, 2012

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Automated Mapping Streaming Applications onto GPUs

SESSION: Research Poster Reception

EVENT TYPE: Posters and Electronic Posters

TIME: 5:15PM - 7:00PM

SESSION CHAIR: Torsten Hoefler

AUTHOR(S):Huynh Phung Huynh, Andrei Hagiescu, Weng-Fai Wong, Rick Goh Siow Mong, Abhishek Ray

ROOM:East Entrance

ABSTRACT:
We describe an efficient and scalable code generation framework that automatically maps general purpose streaming applications onto GPU systems. This architecture-driven framework takes into account the idiosyncrasies of the GPU pipeline and the unique memory hierarchy. The framework has been implemented as a back-end to the StreamIt programming language compiler. First, the generated code increases the effectiveness of the on-chip memory hierarchy by employing a heterogeneous mix of compute and memory access threads. Our scheme goes against the conventional wisdom of GPU programming which is to use a large number of homogeneous threads. Second, we utilise an efficient stream graph partitioning algorithm to handle larger applications and achieve the best performance under the given on-chip memory constraints. Lastly, the framework maps complex applications onto multiple GPUs using a highly effective pipeline execution scheme. Our comprehensive experiments show its scalability and significant speedup compared to a state-of-the-art solution.

Chair/Author Details:

Torsten Hoefler (Chair) - ETH Zurich

Huynh Phung Huynh - Singapore Agency for Science, Technology and Research

Andrei Hagiescu - National University of Singapore

Weng-Fai Wong - National University of Singapore

Rick Goh Siow Mong - Singapore Agency for Science, Technology and Research

Abhishek Ray - Nanyang Technological University

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Automated Mapping Streaming Applications onto GPUs

SESSION: Research Poster Reception

EVENT TYPE:

TIME: 5:15PM - 7:00PM

SESSION CHAIR: Torsten Hoefler

AUTHOR(S):Huynh Phung Huynh, Andrei Hagiescu, Weng-Fai Wong, Rick Goh Siow Mong, Abhishek Ray

ROOM:East Entrance

ABSTRACT:
We describe an efficient and scalable code generation framework that automatically maps general purpose streaming applications onto GPU systems. This architecture-driven framework takes into account the idiosyncrasies of the GPU pipeline and the unique memory hierarchy. The framework has been implemented as a back-end to the StreamIt programming language compiler. First, the generated code increases the effectiveness of the on-chip memory hierarchy by employing a heterogeneous mix of compute and memory access threads. Our scheme goes against the conventional wisdom of GPU programming which is to use a large number of homogeneous threads. Second, we utilise an efficient stream graph partitioning algorithm to handle larger applications and achieve the best performance under the given on-chip memory constraints. Lastly, the framework maps complex applications onto multiple GPUs using a highly effective pipeline execution scheme. Our comprehensive experiments show its scalability and significant speedup compared to a state-of-the-art solution.

Chair/Author Details:

Torsten Hoefler (Chair) - ETH Zurich

Huynh Phung Huynh - Singapore Agency for Science, Technology and Research

Andrei Hagiescu - National University of Singapore

Weng-Fai Wong - National University of Singapore

Rick Goh Siow Mong - Singapore Agency for Science, Technology and Research

Abhishek Ray - Nanyang Technological University

Add to iCal  Click here to download .ics calendar file

Add to Outlook  Click here to download .vcs calendar file

Add to Google Calendarss  Click here to add event to your Google Calendar