Programming many-core systems with GRAMPS

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The era of obtaining increased performance via faster single cores and optimized single-thread programs is over. Instead, forthcoming machines are increasingly parallel and increasingly include nontraditional resources such as programmable GPUs. In this dissertation, we present GRAMPS, a programming model for heterogeneous, commodity, many-core systems that expresses programs as graphs of thread- and data-parallel stages communicating via queues. We validate its viability with respect to four design goals--broad application scope, multi-platform applicability, performance, and tunability--and demonstrate its effectiveness at minimizing the memory consumed by the queues. Through three case studies, we show applications for GRAMPS from domains including interactive graphics, MapReduce, physical simulation, and image processing, and describe GRAMPS runtimes for three many-core platforms: two simulated future rendering platforms and one current multi-core x86 machine. Our GRAMPS runtimes efficiently recognize and exploit the available parallelism while containing the footprint/buffering required by the queues. Finally, we discuss how GRAMPS's scheduling compares to three archetypal representations of popular programming models: task-stealing scheduling, breadth-first scheduling, and static scheduling. We find that when structure is present, GRAMPS's adaptive, dynamic scheduling provides good load-balance with low overhead and its application graph gives it multiple advantages for managing the run-time depths of the queues and their memory footprint.


Type of resource text
Form electronic; electronic resource; remote
Extent 1 online resource.
Publication date 2010
Issuance monographic
Language English


Associated with Sugerman, Jeremy
Associated with Stanford University, Computer Science Department
Primary advisor Hanrahan, P. M. (Patrick Matthew)
Thesis advisor Hanrahan, P. M. (Patrick Matthew)
Thesis advisor Akeley, Kurt
Thesis advisor Rosenblum, Mendel
Advisor Akeley, Kurt
Advisor Rosenblum, Mendel


Genre Theses

Bibliographic information

Statement of responsibility Jeremy Sugerman.
Note Submitted to the Department of Computer Science.
Thesis Thesis (Ph.D.)--Stanford University, 2010.
Location electronic resource

Access conditions

© 2010 by Jeremy Sugerman
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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