MapReduce for the Cell B.E. Architecture
File(s)
Date
2007Author
de Kruijf, Marc
Sankaralingam, Karthikeyan
Publisher
University of Wisconsin-Madison Department of Computer Sciences
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Show full item recordAbstract
MapReduce is a simple and flexible parallel programming
model proposed by Google for large scale data processing
in a distributed computing environment [4]. In this
paper, we present a design and implementation of MapReduce
for the Cell architecture. This model provides a simple
machine abstraction to users, hiding parallelization and
hardware primitives. Our runtime automatically manages
parallelization, scheduling, partitioning and memory transfers.
We study the basic characteristics of the model and
evaluate our runtime�s performance, scalability, and efficiency
for micro-benchmarks and complete applications.We
show that the model is well suited for many applications
that map well to the Cell architecture, and that the runtime
sustains high performance on these applications. For other
applications, we analyze runtime performance and describe
why performance is less impressive. Overall, we find that the
simplicity of the model and the efficiency of our MapReduce
implementationmake it an attractive choice for the Cell platform
specifically and more generally to distributed memory
systems and software-exposed memories.
Permanent Link
http://digital.library.wisc.edu/1793/60614Citation
TR1625