Parallel VSIPL++: An Open Standard Software Library for High-Performance Parallel Signal Processing

Lebak, James; Kepner, Jeremy; Hoffmann, Henry; Rutledge, Edward

doi:10.1109/jproc.2004.840303

Cited by 36 publications

(13 citation statements)

References 12 publications

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“…Adaptive libraries for the related Walsh-Hadamard transform (WHT), based on similar ideas, have been developed in [27]. Reference [28] proposes an object-oriented library standard for parallel signal processing to facilitate porting of both signal processing applications and their performance across parallel platforms.…”

Section: Introductionmentioning

confidence: 99%

SPIRAL: Code Generation for DSP Transforms

et al. 2005

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Abstract-Fast changing, increasingly complex, and diverse computing platforms pose central problems in scientific computing: How to achieve, with reasonable effort, portable optimal performance? We present SPIRAL that considers this problem for the performance-critical domain of linear digital signal processing (DSP) transforms. For a specified transform, SPIRAL automatically generates high performance code that is tuned to the given platform. SPIRAL formulates the tuning as an optimization problem, and exploits the domain-specific mathematical structure of transform algorithms to implement a feedback-driven optimizer. Similar to a human expert, for a specified transform, SPIRAL "intelligently" generates and explores algorithmic and implementation choices to find the best match to the computer's microarchitecture. The "intelligence" is provided by search and learning techniques that exploit the structure of the algorithm and implementation space to guide the exploration and optimization. SPIRAL generates high performance code for a broad set of DSP transforms including the discrete Fourier transform, other trigonometric transforms, filter transforms, and discrete wavelet transforms. Experimental results show that the code generated by SPIRAL competes with, and sometimes outperforms, the best available human tuned transform library code.

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Section: Introductionmentioning

confidence: 99%

SPIRAL: Code Generation for DSP Transforms

et al. 2005

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“…In the image processing domain it is possible to find different examples of parallel libraries, for example VSIPL++ [12], ParHorus [19], PIPT [17]. They provide object-oriented image processing code, and ensure high performance executions; in fact they are improved with performance optimization policy and are compliant to the standard features ensured by a scientific library.…”

Section: Related Workmentioning

confidence: 99%

An Object Interface for Interoperability of Image Processing Parallel Library in a Distributed Environment

Clematis

D’Agostino

Galizia

2005

Image Analysis and Processing – ICIAP 2005

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Abstract. Image processing applications are computing demanding and since a long time much attention has been paid to the use of parallel processing. Emerging distributed and Grid based architectures represent new and well suited platforms that promise the availability of the required computational power. In this direction image processing has to evolve to heterogeneous environments, and a crucial aspect is represented by the interoperability and reuse of available and high performance code. This paper describes our experience in the development of PIMA (GE) 2 , Parallel IMAGE processing GEnoa server, obtained wrapping a library using the CORBA framework. Our aim is to obtain a high level of flexibility and dynamicity in the server architecture with a possible limited overhead. The design of a hierarchy of image processing operation objects and the development of the server interface are discussed.

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“…VSIPL++ allows the user to write high level programs while still achieving performance and preserving the portability of the code across parallel computing hardware platforms. The Parallel Vector, Signal, and Image Processing Library (Parallel VSIPL++) [26] extends VSIPL++ by providing high level C++ array constructs, a simple mechanism for mapping data and functions onto parallel hardware, and a community-defined portable interface. Parallel VSIPL++ supports adaptive optimization at many levels.…”

Section: Introductionmentioning

confidence: 99%