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Programming with actors

Programming with actors. J ö rn W. Janneck Xilinx Research Labs. credits. Dave B. Parlour Xilinx Research Labs Thomas A. Lenart Lund University Robert Esser University of Adelaide. The FPGA Platform:. Huge amounts of fine-grained concurrency.

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Programming with actors

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  1. Programming with actors Jörn W. Janneck Xilinx Research Labs

  2. credits Dave B. Parlour Xilinx Research Labs Thomas A. Lenart Lund University Robert Esser University of Adelaide Xilinx Research Labs

  3. The FPGA Platform: Huge amounts of fine-grained concurrency. ... along with specialized blocks (multipliers, RAM, ALUs, processors...) Xilinx Research Labs

  4. The Problem: Using FPGAs to implement DSP applications requires circuit design expertise. Xilinx Research Labs

  5. The Research Goal: Design and build models and tools that make it possible for application domain experts to program FPGAs with high-quality implementations. Xilinx Research Labs

  6. models and tools What does it take to program with actors? • actors and dataflow as a concurrent model • Cal as the language for writing actors • driver application • tools • code generation • circuits and software and combinations thereof • animation & visualization Xilinx Research Labs

  7. models and tools We are focusing on... ... hardware that can be programmed. ... programming concepts that can be implemented. Xilinx Research Labs

  8. driver applicationMPEG-4 decoder Xilinx Research Labs

  9. driver applicationMPEG-4 decoder • metrics • 60 atomic actors • 22 atomic actor classes • 3307 LOC (Cal) • LOC per actor class between 7 and 2054 • actor constructs • variable token rates • static/cyclostatic rates • data-dependent choice • test for absence of tokens • non-prefix-monotonic actors Xilinx Research Labs

  10. Cal VHDL driver applicationMPEG-4 decoder • development time approx. 2 months. • approximate sizes of various models • Cal: 3,300 LOC • “architectural ” C code: 4,200 LOC • synthesizable VHDL: 15,000 LOC Xilinx Research Labs

  11. code generation2D-IDCT implementation • first step to complete decoder implementation • naive code generator has sufficient language coverage for IDCT compute. 10 classes 200 LOC covers most language features, except...- addressable memory- multicycle actions Xilinx Research Labs

  12. code generation2D-IDCT, version 1 • Starting architecture is very inefficient: 22 multipliers with 12.5% utilization. 1-D AT 1-D Xilinx Research Labs

  13. code generation2D-IDCT, version 2 • interleave row and column streams • pipelined 1D-IDCT • result: • 6 multipliers with 46% utilization • more operator re-use costly in terms of operand routing • >100 Mhz clock Pipelined 1-D IDCT Xilinx Research Labs

  14. code generationsummary • good QoR for “naive” code generator • redesigned model compares favorably with existing VHDL implementations • smaller, faster, simpler to use • HDTV rate • demonstrates strength of programming model, rather than quality of code generator • lots of room for improvement • pipelining, folding Xilinx Research Labs

  15. animation & visualizationactor animation (1/4) input queues Xilinx Research Labs

  16. animation & visualization actor animation (2/4) input queue history Xilinx Research Labs

  17. animation & visualization actor animation (3/4) actor state variables Xilinx Research Labs

  18. animation & visualization actor animation (4/4) action selection status Xilinx Research Labs

  19. outlook • improved hardware code generation • language coverage • optimizations • software code generation • analysis and optimization tools • debugging/visualization tools • alternative entry mechanisms • “VisualCal” Xilinx Research Labs

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