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PfeLib—A Performance Primitives Library for Embedded Vision

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Abstract

This paper presents our work on PfeLib—a high performance software library for image processing and computer vision algorithms for an embedded system. The main target platform for PfeLib is the TMS320C6000 series of digital signal processors (DSPs) from Texas instruments. PfeLib contains several new approaches for problems that are typical when developing software for embedded systems. We propose a method for image data transfer from a development host (PC) to an embedded system for test and verification. This enables step-by-step performance optimizations directly on the target platform. An optimization procedure is described that illustrates our approach for obtaining the best possible DSP performance with a reasonable development effort. Speedup improvement factors of up to 16 were achieved. Also, the problem of the limited on-chip memory on DSPs is addressed by a novel double buffering method using direct memory access (DMA), called resource optimized slicing (ROS-DMA). ROS-DMA is intended to be used instead of L2 cache and it is a core component of PfeLib—it achieves up to six times faster image processing as compared to using L2 cache.

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Correspondence to Christian Zinner.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Keywords

  • Embed System
  • Digital Signal Processor
  • Software Library
  • Texas Instrument
  • Direct Memory Access