1. Embedded Systems & Parallel Programming

2. - 2 - P. Marwedel, Univ. Dortmund/Informatik 12 + ICD/ES, 2007 Universität Dortmund A view on embedded systems (1)

3. - 3 - P. Marwedel, Univ. Dortmund/Informatik 12 + ICD/ES, 2007 Universität Dortmund A view on embedded systems (2) Main reason for buying is not information processing Embedded systems (ES) = information processing systems embedded into a larger product Areas: 1.High performance signal processing 2.Control intensive applications 3.High-safety application Tight power constraints, especially for mobile applications

4. - 4 - P. Marwedel, Univ. Dortmund/Informatik 12 + ICD/ES, 2007 Universität Dortmund Inherent Power Efficiency © Hugo De Man, IMEC, 2007 GOPs/J

5. - 5 - P. Marwedel, Univ. Dortmund/Informatik 12 + ICD/ES, 2007 Universität Dortmund Examples of Embedded Processors © Hugo De Man, IMEC, 2007 ½ of IPE; obviously heterogeneous processors

6. - 6 - P. Marwedel, Univ. Dortmund/Informatik 12 + ICD/ES, 2007 Universität Dortmund FAUST chip architecture 4G mobile application 20 nodes with 23 IPs are connected by a network 8MG / 0.13μ CMOS technology (STMicroelectronics) NoC Example t (mem. access) « t (communic.) try to avoid buffering of messages!

7. - 7 - P. Marwedel, Univ. Dortmund/Informatik 12 + ICD/ES, 2007 Universität Dortmund Programming models for parallel embedded systems (1)

8. - 8 - P. Marwedel, Univ. Dortmund/Informatik 12 + ICD/ES, 2007 Universität Dortmund Problems with classical CS abstractions Even the core 20th-century notion of computable is at odds with the requirements of embedded software. In this notion, useful computation terminates, but termination is undecidable. In embedded software, termination is failure-yet to get predictable timing, subcomputations must decidably terminate. Ed Lee: Absolutely positively on time: What would it take? IEEE Computer, July, 2005 Finally an end to von-Neumann specifications?

9. - 9 - P. Marwedel, Univ. Dortmund/Informatik 12 + ICD/ES, 2007 Universität Dortmund Toward different models of computation

10. - 10 - P. Marwedel, Univ. Dortmund/Informatik 12 + ICD/ES, 2007 Universität Dortmund Other models of computation & approaches Various types of tasks graphs Kahn process networks Synchronous dataflow Partial differential equations Event queues Generated software …. How much of this is used in practice already?

11. - 11 - P. Marwedel, Univ. Dortmund/Informatik 12 + ICD/ES, 2007 Universität Dortmund Generated software examples After the successful use of SCADE on the A340, AIRBUS adopted it for several A380 projects http://www.esterel-technologies.com/ technology/success-stories/airbus.html Production code generation directly from MATLAB®/Simulink®/Stateflow® ANSI C code with the efficiency of handwritten code Optimizations for individual processors Built-in simulation and testing SCADE DSPACE Targetlink http://www.dspace.ltd.uk/ww/en/ltd/home/products/sw/pcgs/targetli.cfm

12. - 12 - P. Marwedel, Univ. Dortmund/Informatik 12 + ICD/ES, 2007 Universität Dortmund Task to Processor Mapping (1) © L. Thiele et al.

13. - 13 - P. Marwedel, Univ. Dortmund/Informatik 12 + ICD/ES, 2007 Universität Dortmund Task to Processor Mapping (2)

14. - 14 - P. Marwedel, Univ. Dortmund/Informatik 12 + ICD/ES, 2007 Universität Dortmund Task to Processor Mapping (3)

15. - 15 - P. Marwedel, Univ. Dortmund/Informatik 12 + ICD/ES, 2007 Universität Dortmund Task to Processor Mapping (4)

16. - 16 - P. Marwedel, Univ. Dortmund/Informatik 12 + ICD/ES, 2007 Universität Dortmund Task to Processor Mapping (5)

17. - 17 - P. Marwedel, Univ. Dortmund/Informatik 12 + ICD/ES, 2007 Universität Dortmund 2nd example

18. - 18 - P. Marwedel, Univ. Dortmund/Informatik 12 + ICD/ES, 2007 Universität Dortmund Demonstrated parallelism: SymTA/S Screenshot

19. - 19 - P. Marwedel, Univ. Dortmund/Informatik 12 + ICD/ES, 2007 Universität Dortmund Parallel Accelerator: Triscend A7 CSoC ARM7TDMI + FPGA Source: © Triscend

20. - 20 - P. Marwedel, Univ. Dortmund/Informatik 12 + ICD/ES, 2007 Universität Dortmund Parallel Accelerator: Chameleon C/Verilog –based reconfigurable platform Application of HPC techniques?

21. - 21 - P. Marwedel, Univ. Dortmund/Informatik 12 + ICD/ES, 2007 Universität Dortmund Conclusion Parallel embedded systems are a reality Architectures include heterogeneous MPSoCs (also NoCs), parallel accelerators. Multiple threads a potential problem Introduction of new models of computation realistic Higher level programming acceptable Parallel execution existing standard for ECUs for MPSoCs, NoCs for accelerators Situation different from HPC