SCHEDULE: NOV 10-16, 2012
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Designing a Unified Programming Model for Heterogeneous Machines
SESSION: Locality in Programming Models and Runtimes
EVENT TYPE: Papers
TIME: 4:30PM - 5:00PM
SESSION CHAIR: Milind Kulkarni
AUTHOR(S):Michael Garland, Manjunath Kudlur, Yili Zheng
ROOM:255-EF
ABSTRACT:
While high-efficiency machines are increasingly embracing heterogeneous
architectures and massive multithreading, contemporary mainstream
programming languages reflect a mental model in which processing
elements are homogeneous, concurrency is limited, and memory is a flat
undifferentiated pool of storage. Moreover, the current state of the
art in programming heterogeneous machines tends towards using separate
programming models, such as OpenMP and CUDA, for different portions of
the machine. Both of these factors make programming emerging
heterogeneous machines unnecessarily difficult.
We describe the design of the Phalanx programming model, which seeks to
provide a unified programming model for heterogeneous machines. It
provides constructs for bulk parallelism, synchronization, and data
placement which operate across the entire machine. Our prototype
implementation is able to launch and coordinate work on both CPU and GPU
processors within a single node, and by leveraging the GASNet runtime,
is able to run across all the nodes of a distributed-memory machine.
Chair/Author Details:
Milind Kulkarni (Chair) - Purdue University
Michael Garland - NVIDIA
Manjunath Kudlur - NVIDIA
Yili Zheng - Lawrence Berkeley National Laboratory
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Designing a Unified Programming Model for Heterogeneous Machines
SESSION: Locality in Programming Models and Runtimes
EVENT TYPE:
TIME: 4:30PM - 5:00PM
SESSION CHAIR: Milind Kulkarni
AUTHOR(S):Michael Garland, Manjunath Kudlur, Yili Zheng
ROOM:255-EF
ABSTRACT:
While high-efficiency machines are increasingly embracing heterogeneous
architectures and massive multithreading, contemporary mainstream
programming languages reflect a mental model in which processing
elements are homogeneous, concurrency is limited, and memory is a flat
undifferentiated pool of storage. Moreover, the current state of the
art in programming heterogeneous machines tends towards using separate
programming models, such as OpenMP and CUDA, for different portions of
the machine. Both of these factors make programming emerging
heterogeneous machines unnecessarily difficult.
We describe the design of the Phalanx programming model, which seeks to
provide a unified programming model for heterogeneous machines. It
provides constructs for bulk parallelism, synchronization, and data
placement which operate across the entire machine. Our prototype
implementation is able to launch and coordinate work on both CPU and GPU
processors within a single node, and by leveraging the GASNet runtime,
is able to run across all the nodes of a distributed-memory machine.
Chair/Author Details:
Milind Kulkarni (Chair) - Purdue University
Michael Garland - NVIDIA
Manjunath Kudlur - NVIDIA
Yili Zheng - Lawrence Berkeley National Laboratory
Click here to download .ics calendar file