1. CS curricula update proposed: by adding Reconfigurable Computing Reiner Hartenstein TU Kaiserslautern EAB meeting, Philadelphia,1 Nov 2005

2. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 2 Computing Curricula 2004 (1) # Reconfigurable Computing Embedded Systems

3. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 3 Computing Curricula 2004 (2) #

4. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 4 Computing Curricula 2004 (3) 2.2.1.

5. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 5 Computing Curricula 2004 (4) EECECSSE

6. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 6 Computing Curricula 2004 (5) EECECSSE SOFTWARE HARDWARE

7. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 7 Computing Curricula 2004 (6) EECECSSE SOFTWARE HARDWARE CONFIGWARE MORPHWARE

8. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 8 What means Morphware, Configware ? EECECSSE CONFIGWARE MORPHWARE

9. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 9 Paradigm Shifts: Nick Tredennick‘s view (1) algorithms variable resources fixed instruction-stream- based computing: µ processor Software instruction-stream algorithms variable only a single programming source needed The Mainframe Age Software Engineering

10. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 10 algorithms variable resources variable data-stream-based reconfigurable computing: reconfigurable accelerators reconfigurable accelerators Paradigm Shifts: Nick Tredennick‘s view (2) Configware resources variable Flowware data-stream algorithms variable Reconfigurable Computing Configware Engineering 2 programming source needed

11. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 11 Paradigm Shifts: Nick Tredennick‘s view (3) algorithms variable resources fixed instruction-stream- based computing: algorithms variable resources variable data-stream-based reconfigurable computing: The Morphware Age data-stream instruction-stream Configware resources variable Flowware Software 3 sources accelerators µ processor programmable algorithms variable

12. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 12 Compilation: Software vs. Configware source program software compiler software code Software Engineering configware code mapper configware compiler scheduler flowware code source „ program “ Configware Engineering placement & routing data C, FORTRAN MATHLAB

13. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 13 Co-Compilation software compiler software code Software / Configware Co-Compiler configware code mapper configware compiler scheduler flowware code data C, FORTRAN, MATHLAB

14. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 14 Code Destinations Program Counter (structural) Data Counter(s) software compiler software code Software / Configware Co-Compiler configware code mapper configware compiler scheduler flowware code data C, FORTRAN, MATHLAB

15. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 15 Program Counter (structural) Data Counter(s) software compiler software code Software / Configware Co-Compiler configware code mapper configware compiler scheduler flowware code data C, FORTRAN, MATHLAB Inter face

16. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 16 Hardwired anti machine (for instance: systolic array) Program Counter software compiler software code Software / Flowware Co-Compiler Data Counter(s) flowware compiler scheduler flowware code data C, FORTRAN, MATHLAB Inter face

17. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 17 >> Outline << Pervasiveness & Strategic Dimension Proposing an update of CS curricula Conclusion Details of the curricula update proposal Illustrating the dual paradigm model Appendices

18. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 18 Reconfigurable Computing (RC) and FPGA in the media ##### Design Starts until 2010: from 80,000 to 110,000 [Dataquest] June 2005 fastest growing segment of the semiconductor market: 4 billion US-$ [Dataquest]

19. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 19 going into every application area

20. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 20 one-click search http://hartenstein.de/pervasiveness.html

21. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 21 intensive conference activities found by Google: (October 2005) for a detailed list of RC-related conferences see my enclosed proposal for a new magazine

22. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 22 example conference series http://www.ece.lsu.edu/vaidy/raw06/

23. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 23 FPGAs for Reconfigurable Computing (RC) compared to µProcessors (intel,...): speed-up by factors up to x100 and more Running and airconditioning: reducing the electricity bill up to millions of $ per year FPGAs reduce power dissipation: MOPS / milliWatts by a factor of x10 *) Field-Programmable Gate Array even supercomputing goes FPGA * (sgi, Cray, …)

24. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 24 Exponential Growth & Strategic Dimension Reconfigurable Computing (RC) became mainstream years ago, not only in Embedded Systems Economic importance has grown exponentially. Strategic dimension has been appreciated. Education is an essential factor to solve the current complexity crisis and creating a qualified workforce

25. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 25 Morphware Age Our students are not even aware, that we all now live in the Morphware Age, not in the Mainframe Age Changing this will make CS much more fascinating

26. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 26 #### 10/24/05; Vol. 24 No. 31 --- Ask the Professor: Reconfigurable Computing - By Joab Jackson -- GCN Staff The computer science academic community has investigated the use of field-programmable gate arrays for quite some time. To get beyond the product hype, we interviewed associate professor Kris Gaj of George Mason University’s Department of Electrical and Computer Engineering, who has long been involved in reconfigurable computing. GCN: We’ve heard claims of anything from a 40- to 20,000-fold increase in performance speeds over standard commodity chips. What kind of improvement can users expect from a well-engineered program? Gaj: Our group has developed multiple applications for a few reconfigurable computers, from SRC, SGI and Cray. We have seen speed-ups compared to a single traditional microprocessor (Pentium 4) anywhere from none to over 1,000 [times]. The speed-up really depends on a particular task, and how well this task can be divided into smaller operations that can execute in parallel. [The claim of a] 20,000-times speed-up is probably an exaggeration, unless you use a lot of FPGAs, but such machines would really cost a fortune. GCN: Where is that performance improvement coming from? Gaj: A microprocessor executes instructions sequentially, one by one. A single instruction does only a small part of the job, so it takes a long time to complete the entire sequence of such instructions constituting the program. Additionally, a microprocessor cannot be reconfigured, so a lot of resources may need to be allocated for functions that will never be used by a particular program. An FPGA may execute multiple operations in parallel. Since it is reconfigurable, you do not need to waste any resources, such as circuit area, for implementing operations that are not used by a given program. The contents of an FPGA may also change on the fly, i.e., during the program execution, so you do not need to have all resources tied up at the beginning of computations. GCN: Do you predict companies like Cray and SGI can bring FPGA computing to a broader audience of users? Gaj: I would not expect an FPGA in every PC at home anytime soon. For a couple of years, the primary use of reconfigurable computers will be for scientific computations, such as weather simulations, space exploration, human genome project and simulation of nuclear reactions. These machines should be treated as an alternative for traditional supercomputers, and may eventually outperform and replace some or most of them. For bringing FPGAs to a broader audience, the prices must drop by at least an order of magnitude, and tools must be developed that make the programming of these machines much easier than it is right now. Additionally, in many cases, traditional microprocessors would be completely sufficient for [a] majority of personal and business applications.Joab Jackson http://www.gcn.com/24_31/tech-report/37341-1.html

27. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 27 >> Proposing an update of CS curricula << Pervasiveness & Strategic Dimension Proposing an update of CS curricula Conclusion Details of the curricula update proposal Illustrating the dual paradigm model Appendices

28. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 28 Importance of embedded FPGAs almost 90% of all software is implemented for embedded systems embedded software doubles every 10 months FPGAs are inevitable for embedded systems

29. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 29 Configware and CS curricula to-day, typical CS graduates are not qualified for this job market hardware / configware / software partitioning problems cannot be handled … the de facto basic model is a dual-paradigm system, however, not von-Neumann-only … the florishing configware industry is the younger brother of the software industry

30. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 30 difficult RC education fragmentation into many application areas: teaching their own tricks – no common model unstructured view onto creators‘ architectures, advertized by catchy terms („we are creative“) no common terminology: maybe, managers do not understand what you are talking about confusing mind set, no computing viewpoint: not seen as a common fundamental paradigm no clear hierachical view by abstraction levels

31. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 31 CS urgently needed for the therapy teach already freshmen by dual-paradigm model integrative undergraduate lab courses needed teach code refactoring & algorithmic cleverness CS is the only right point of view to fix all this

32. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 32 Stop declining enrollment making CS more fascinating: innovation by RC providing RC and embedded system qualifications to our students by common models – not tricks CS is the only right place to provide all this reversing our membership development trend ?

33. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 33 for course implementation technology 20 years old, invented 1984 (Xilinx) software–to-configware migration: all enabling methodologies available, some published in the 70ies or 80ies

34. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 34 new workshop series deadline for submissions: November 27, 2005 http://helios.informatik.uni-kl.de/RCeducation/

35. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 35 other curriculum recommendations Real-Time Systems (Sweden) Recommendations for Designing New ICT Curricula WESE - Workshop on Embedded Systems Education WESE Chess - Center for Hybrid and Embedded Software Systems (courses in embedded systems) (EU) Graduate Curriculum on Embedded Software and Systems Advanced Real Time Systems

36. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 36 Reconfigurable Computing ? in these recommendations RC is not an issue so far: action needed by CS

37. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 37 >> Conclusion << Pervasiveness & Strategic Dimension Proposing an update of CS curricula Conclusion Details of the curricula update proposal Illustrating the dual paradigm model Appendices

38. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 38 Conclusions (1) We need curricula to cope with the clash of cultures by merging all different backgrounds in a systematic way CS curricula for unifying the foundations We need innovative lectures and lab courses integrating reconfigurable computing into progressive CS curricula. We need to counter the current education trend toward specialization

39. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 39 Conclusions (2) CS curricula should adopt the dichotomy of software engineering and configware engineering Application domain‘s point of views cannot replace the urgently needed CS-based efforts …….. CS undergraduate curricula must switch from von-Neuman-only to the dual paradigm model Only CS is qualified to be conductor of RC-related curriculum recommendations and implementation

40. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 40 thank you

41. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 41 END

42. © 2005, reiner@hartenstein.de http://hartenstein.de TU Kaiserslautern 42 --