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  • The traditional approach to IP core design is to use simulations with test vectors. This is not feasible when dealing with complex function cores such as the Image Segmentation case-study algorithm in this paper. An algorithm developer needs to carry out experiments on large real-world data sets, with fast turn-around times, and in real time to facilitate performance tuning and incremental development. Previously we proposed a methodology called Application-Specific Vector Processor (ASVP). The ASVP approach first constructs a programmable architecture customized for a given application, then employs software techniques to develop firmware that implements the algorithm. In our setting we employ an embedded simple scalar CPU (8-bit PicoBlaze 3) to control a floating-point vector processing unit (VPU) by issuing wide (horizontally encoded) instructions to it. In this work we dramatically reduce the overhead of the wide-instruction issue (in one case by 13x) by implementing a new two-level configuration table.
  • The traditional approach to IP core design is to use simulations with test vectors. This is not feasible when dealing with complex function cores such as the Image Segmentation case-study algorithm in this paper. An algorithm developer needs to carry out experiments on large real-world data sets, with fast turn-around times, and in real time to facilitate performance tuning and incremental development. Previously we proposed a methodology called Application-Specific Vector Processor (ASVP). The ASVP approach first constructs a programmable architecture customized for a given application, then employs software techniques to develop firmware that implements the algorithm. In our setting we employ an embedded simple scalar CPU (8-bit PicoBlaze 3) to control a floating-point vector processing unit (VPU) by issuing wide (horizontally encoded) instructions to it. In this work we dramatically reduce the overhead of the wide-instruction issue (in one case by 13x) by implementing a new two-level configuration table. (en)
Title
  • Reducing Instruction Issue Overheads in Application-Specific Vector Processors
  • Reducing Instruction Issue Overheads in Application-Specific Vector Processors (en)
skos:prefLabel
  • Reducing Instruction Issue Overheads in Application-Specific Vector Processors
  • Reducing Instruction Issue Overheads in Application-Specific Vector Processors (en)
skos:notation
  • RIV/67985556:_____/12:00380442!RIV13-MSM-67985556
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  • P(7H10001)
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  • 164483
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  • RIV/67985556:_____/12:00380442
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  • custom accelerators; vector processing; FPGA; DSP (en)
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  • [ED5F06249C81]
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  • Cesme
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  • Izmir
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  • Proceedings of the 15th Euromicro Conference on Digital System Design, DSD 2012
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  • Daněk, Martin
  • Kohout, Lukáš
  • Sýkora, Jaroslav
  • Honzík, P.
  • Bartosinski, Roman
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http://linked.open.../riv/zahajeniAkce
number of pages
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  • Conference Publishing Services
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  • 978-0-7695-4798-5
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