1. - 1 - Embedded systems: processing Embedded System Hardware Embedded system hardware is frequently used in a loop („hardware in a loop“): actuators

2. - 2 - Embedded systems: processing Summary: Information processing 1.ASICs 2.Processors Energy efficient Code-size efficient Run-time efficient Special features of DSP processors Multimedia instructions Very long instruction word machines 3.Reconfigurable hardware 4.Memory 1.ASICs 2.Processors Energy efficient Code-size efficient Run-time efficient Special features of DSP processors Multimedia instructions Very long instruction word machines 3.Reconfigurable hardware 4.Memory

3. - 3 - Embedded systems: processing Reconfigurable Logic Full custom chips may be too expensive, software may be too slow.  Use of configurable hardware; most common form: field programmable gate arrays (FPGAs) Considered e.g. for configuring mobile phone according to local standards; Fast “object recognition”. Example: Xilinx Virtex II FPGAs, Altera Stratix Full custom chips may be too expensive, software may be too slow.  Use of configurable hardware; most common form: field programmable gate arrays (FPGAs) Considered e.g. for configuring mobile phone according to local standards; Fast “object recognition”. Example: Xilinx Virtex II FPGAs, Altera Stratix

4. - 4 - Embedded systems: processing Floor-plan of VIRTEX II FPGAs

5. - 5 - Embedded systems: processing Virtex II Configurable Logic Block (CLB)

6. - 6 - Embedded systems: processing Virtex II Pro Devices include up to 4 PowerPC processor cores [© and source: Xilinx Inc.: Virtex-II Pro™ Platform FPGAs: Functional Description, Sept. 2002, //www.xilinx.com]

7. - 7 - Embedded systems: processing Memory For the memory, efficiency is again a concern: fast (latency and throughput); predictable timing energy efficiency size cost other attributes (volatile vs. persistent, etc) For the memory, efficiency is again a concern: fast (latency and throughput); predictable timing energy efficiency size cost other attributes (volatile vs. persistent, etc)

8. - 8 - Embedded systems: processing Access-times will be a problem Speed gap between processor and main DRAM increases 2 4 8 245 Speed years CPU (1.5-2 p.a.) DRAM (1.07 p.a.) 31 early 60ties (Atlas): page fault ~ 2500 instructions 2002 (2 GHz µP): access to DRAM ~ 500 instructions  penalty for cache miss soon same as for page fault in Atlas early 60ties (Atlas): page fault ~ 2500 instructions 2002 (2 GHz µP): access to DRAM ~ 500 instructions  penalty for cache miss soon same as for page fault in Atlas [P. Machanik: Approaches to Addressing the Memory Wall, TR Nov. 2002, U. Brisbane]  2x every 2 years 1 0

9. - 9 - Embedded systems: processing Access times and energy consumption increases with the size of the memory Example (CACTI Model): "Currently, the size of some applications is doubling every 10 months" [STMicroelectronics, Medea+ Workshop, Stuttgart, Nov. 2003]

10. - 10 - Embedded systems: processing How much of the energy consumption of a system is memory-related? Mobile PC Thermal Design (TDP) System Power Note: Based on Actual Measurements 600/500 MHz uP 37% LCD 10" 19% HDD 9% Memory+Graphics 12% Power Supply 10% Other 13% Mobile PC Average System Power 600/500 MHz uP 13% LCD 10" 30% HDD 19% Memory+Graphics 15% Power Supply 10% Other 13% CPU Dominates Thermal Design Power Multiple Platform Components Comprise Average Power [Courtesy: N. Dutt; Source: V. Tiwari]

11. - 11 - Embedded systems: processing CPU Power Dissipation IEEE Journal of SSC Nov. 96 Proceedings of ISSCC 94 Based on slide by and ©: Osman S. Unsal, Israel Koren, C. Mani Krishna, Csaba Andras Moritz, University of Massachusetts, Amherst, 2001 42%/40% again memory-related !

12. - 12 - Embedded systems: processing Predictability is a problem Embedded system systems are often real-time systems: –Have to guarantee meeting timing constraints. Predictability: For satisfying timing constraints in hard real- time systems, predictability is the most important concern; pre run-time scheduling is often the only practical means of providing predictability in a complex system [Xu, Parnas]  Time-triggered, statically scheduled operating systems What about memory accesses? –Currently available caches don‘t solve the problem: Improve the average case behavior Use “non-deterministic” cache replacement algorithms  Scratch-pad/tightly coupled memory based predictability Embedded system systems are often real-time systems: –Have to guarantee meeting timing constraints. Predictability: For satisfying timing constraints in hard real- time systems, predictability is the most important concern; pre run-time scheduling is often the only practical means of providing predictability in a complex system [Xu, Parnas]  Time-triggered, statically scheduled operating systems What about memory accesses? –Currently available caches don‘t solve the problem: Improve the average case behavior Use “non-deterministic” cache replacement algorithms  Scratch-pad/tightly coupled memory based predictability

13. - 13 - Embedded systems: processing Hierarchical memories using scratch pad memorys (SPM) Address space ARM7TDMI cores, well-known for low power consumption scratch pad memory 0 FFF.. main SPM processor Hierarchy Example no tag memory

14. - 14 - Embedded systems: processing Scratchpad vs. main memory currents Example: Atmel ARM-Evaluation board Processor SPM (On-chip) Main Memory (on board) current reduction: / 3.02 current reduction: / 3.02

15. - 15 - Embedded systems: processing Why not just use a cache ? [P. Marwedel et al., ASPDAC, 2004] 1.Predictability? Worst case execution time (WCET) may be large

16. - 16 - Embedded systems: processing Why not just use a cache ? (2) [R. Banakar, S. Steinke, B.-S. Lee, 2001] 2.Energy for parallel access of sets, in comparators, muxes.

17. - 17 - Embedded systems: processing Embedded System Hardware Embedded system hardware is frequently used in a loop („hardware in a loop“): actuators

18. - 18 - Embedded systems: processing Digital-to-Analog (D/A) Converters Various types, can be quite simple, e.g.:

19. - 19 - Embedded systems: processing Due to Kirchhoff‘s laws: Current into Op-Amp=0: Hence: Finally: Output voltage  no. represented by x

20. - 20 - Embedded systems: processing Possible to reconstruct analog value from digitized value? According to Nyquist theorem: Analog input to sample-and-hold can be precisely reconstructed from its output, provided that sampling proceeds at  double of the highest frequency found in the input voltage and provided voltages remain analog. Digitizing values in the A/D generates additional uncertainty preventing precise reconstruction of initial values. Can be modeled as additional noise. According to Nyquist theorem: Analog input to sample-and-hold can be precisely reconstructed from its output, provided that sampling proceeds at  double of the highest frequency found in the input voltage and provided voltages remain analog. Digitizing values in the A/D generates additional uncertainty preventing precise reconstruction of initial values. Can be modeled as additional noise. S/H A/D-converterD/A-converter = ? Inter- polate

21. - 21 - Embedded systems: processing Embedded System Hardware Embedded system hardware is frequently used in a loop („hardware in a loop“): actuators

22. - 22 - Embedded systems: processing Actuators and output Huge variety of actuators and output devices, impossible to present all of them. Microsystems motors as examples (© MCNC): (© MCNC)

23. - 23 - Embedded systems: processing Actuators and output (2) Courtesy and ©: E. Obermeier, MAT, TU Berlin