Jerker Bengtsson
Bertil Svensson
Abstract
The programming complexity of increasingly parallel processors calls for new tools that assist programmers in utilising the parallel hardware resources. In this paper we present a set of models that we have developed as part of a tool for mapping dataflow graphs onto manycores. One of the models captures the essentials of manycores identified as suitable for signal processing, and which we use as target for our algorithms. As an intermediate representation we introduce timed configuration graphs, which describe the mapping of a model of an application onto a machine model. Moreover, we show how a timed configuration graph by very simple means can be evaluated using an abstract interpretation to obtain performance feedback. This information can be used by our tool and by the programmer in order to discover improved mappings.
- C. Brooks, E. A. Lee, X. Liu, S. Neuendorffer, Y. Zhao, and H. Zheng. Heterogeneous Concurrent Modeling and Design in Java (Volume 1: Introduction to Ptolemy II). Technical Report UCB/EECS-2008-28, EECS Dept., University of California, Berkeley, Apr 2008.Google Scholar
- D. Culler, R. Karp, and D. Patterson. LogP: Towards a Realistic Model of Parallel Computation. In Proc. of ACM SIGPLAN Symposium on Principles and Practices of Parallel programming, May 1993. Google ScholarDigital Library
- M. I. Gordon, W. Thies, and S. Amarasinghe. Exploiting Coarse-Grained Task, Data, and Pipeline Parallelism in stream programs. In Proc. of Twelfth Int'l. Conf. on Architectural Support for Programming Languages and Operating Systems, 2006. Google ScholarDigital Library
- G. Kahn. The Semantics of a Simple Language for Parallel Programming. In J. L. Rosenfeld, editor, IFIP Congress 74, pages 471--475, Stockholm, Sweden, August 5-10 1974. North-Holland Publishing Company.Google Scholar
- R. M. Karp and R. E. Miller. Properties of a Model for Parallel Computations:Determinancy, Termination, Queueing. SIAM Journal of Applied Mathematics, 14(6):1390--1411, November 1966.Google ScholarCross Ref
- E. A. Lee and D. G. Messerschmitt. Static Scheduling of Synchronous Data Flow Programs for Signal Processing. IEEE Trans. on Computers, January 1987. Google ScholarDigital Library
- C. A. Moritz, D. Yeung, and A. Agarwal. SimpleFit: A Framework for Analyzing Design Tradeoffs in Raw Architectures. IEEE Trans. on Parallel and Distributed Systems, 12(6), June 2001. Google ScholarDigital Library
- T. M. Parks. Bounded Scheduling of Process Networks. PhD thesis, EECS Dept., University of California, Berkeley, Berkeley, CA, USA, 1995. Google ScholarDigital Library
- H. Sahlin. Introduction and overview of LTE Baseband Algorithms. Powerpoint presentation, Baseband research group, Ericsson AB, February 2007.Google Scholar
- M. B. Taylor, J. Kim, J. Miller, D. Wentzlaff, F. Ghodrat, B. Greenwald, H. Hoffman, P. Johnson, J.-W. Lee, W. Lee, A. Ma, A. Saraf, M. Seneski, N. Shnidman, V. Strumpen, M. Frank, S. Amarasinghe, and A. Agarwal. The Raw Microprocessor: A Computational Fabric for Software Circuits and General-Purpose Programs. IEEE Micro, 22(2):25--35, 2002. Google ScholarDigital Library
- M. B. Taylor, W. Lee, S. P. Amarasinghe, and A. Agarwal. Scalar Operand Networks. IEEE Trans. on Parallel and Distributed Systems, 16(2):145--162, 2005. Google ScholarDigital Library
Index Terms
- A domain-specific approach for software development on Manycore platforms
Recommendations
Parallelization of stochastic bounds for Markov chains on multicore and manycore platforms
The author demonstrates the methodology for parallelizing of finding stochastic bounds for Markov chains on multicore and manycore platforms. The stochastic bounds algorithm for Markov chains with the sparse matrices is investigated, thus needing a lot ...
A cluster for CS education in the manycore era
SIGCSE '11: Proceedings of the 42nd ACM technical symposium on Computer science educationTraditional Beowulf clusters have been homogeneous platforms for distributed-memory MIMD parallelism. However, the shift to multicore architectures has made shared-memory MIMD parallelism increasingly important, and inexpensive manycore GPGPUs have ...
Porting the COSMO Weather Model to Manycore CPUs
PASC '19: Proceedings of the Platform for Advanced Scientific Computing ConferenceWeather and climate simulations are a major application driver in high-performance computing (HPC). With the end of Dennard scaling and Moore's law, the HPC industry increasingly employs specialized computation accelerators to increase computational ...
Comments