1. University of Michigan Electrical Engineering and Computer Science 1 An Architecture Framework for Transparent Instruction Set Customization in Embedded Processors Nathan Clark, Jason Blome, Michael Chu, Scott Mahlke, Stuart Biles*, Krisztián Flautner* Advanced Computer Architecture Lab, University of Michigan *ARM Ltd.

2. University of Michigan Electrical Engineering and Computer Science 2 The Expression Gap RISC ISAs are lowest common denominator ► Don’t match applications’ computation ► Don’t match hardware capabilities Need efficient execution Impressive design wins through customization ► Performance, power, etc.

3. University of Michigan Electrical Engineering and Computer Science 3 Customization Gains: Performance 0 0.5 1 1.5 2 2.5 3 3.5 4 3DesAESBlowfishMd5Rc4SHA Speedup OptimoDE (5 Issue VLIW, 333 MHz) OptimoDE + Custom ISA

4. University of Michigan Electrical Engineering and Computer Science 4 Demanding parts of applications run on special hardware New instructions use the special hardware Traditional ISA Customization XOR MPY LD XOR SHR XOR MOV AND CUSTOM MPY LD SHR CPU Custom Hardware

5. University of Michigan Electrical Engineering and Computer Science 5 Objectives of Transparent ISA Customization Increase execution efficiency of processors Architecture framework for subgraph acceleration ► Create a pipeline with fixed interface ► Design and verify once Support Plug-and-Play style accelerators CISC on Demand

6. University of Michigan Electrical Engineering and Computer Science 6 Traditional vs. Transparent Customization Traditional Significant ISA change High NRE ► Verification ► Masks Control placed in binary ► Software migration No legacy codes Transparent No ISA change Baseline CPU unchanged ► Hardware generates control ► Eases software burden Forward compatible

7. University of Michigan Electrical Engineering and Computer Science 7 Architecture Framework Compiler Standard Pipeline … Subg. … Subg. … Application Subgraph Execution Unit InputsOutputs Control Generation Instructions Augments Instruction Stream 1. 4. 3. 2.

8. University of Michigan Electrical Engineering and Computer Science 8 Configurable Compute Array (CCA) Array of function units Two types of FUs: arith/logic, logic 82% of important subgraphs Crossbar between rows 3.19ns critical path 0.61mm 2 in 0.13  I1I2I1I3I4 O1O2

9. University of Michigan Electrical Engineering and Computer Science 9 Architecture Framework Compiler Standard Pipeline … Subg. … Subg. … Application Subgraph Execution Unit InputsOutputs Control Generation Instructions Augments Instruction Stream 1. 4. 3. 2.

10. University of Michigan Electrical Engineering and Computer Science 10 Compiler Identify and delineate subgraphs “Procedural Abstraction” – used in compression

11. University of Michigan Electrical Engineering and Computer Science 11 Architecture Framework Compiler Standard Pipeline … Subg. … Subg. … Application Subgraph Execution Unit InputsOutputs Control Generation Instructions Augments Instruction Stream 1. 4. 3. 2.

12. University of Michigan Electrical Engineering and Computer Science 12 I1 Control Generation I1I2I3I4 O1O2 Subg: AND r3, r1, #-4 SEXT r2, r4 AND r2, r2, #3 OR r3, r3, r2 RET I1I2

13. University of Michigan Electrical Engineering and Computer Science 13 Architecture Framework Compiler Standard Pipeline … Subg. … Subg. … Application Subgraph Execution Unit InputsOutputs Control Generation Instructions Augments Instruction Stream 1. 4. 3. 2.

14. University of Michigan Electrical Engineering and Computer Science 14 Pipeline Interface

15. University of Michigan Electrical Engineering and Computer Science 15 Evaluation Ported Trimaran compiler to ARM ISA ► Subgraph identification engine Synthesized control generator and accelerator SimpleScalar configured as ARM926EJ-S ► 5 stage pipe, 250 MHz ► 1 cycle 16k I/D caches ► Single issue ► 1 cycle subgraph execution latency

16. University of Michigan Electrical Engineering and Computer Science 16 Performance Results 1 1.5 2 2.5 3 3.5 4 4.5 5 164.gzip 181.mcf 197.parser 256.bzip2 300.twolf cjpeg djpeg epic unepic g721encodeg721decode gsmencodegsmdecode pegwitencpegwitdec rawcaudio rawdaudio blowfish md5 rc4 Rijndael sha Speedup SPECintMediaBenchEncryption 6.51 1.6 IPC on a single-issue core

17. University of Michigan Electrical Engineering and Computer Science 17 Plug-and-Play Benefits Baseline Area: 0.61mm 2 Baseline Speedup: 1.8

18. University of Michigan Electrical Engineering and Computer Science 18 Effect of CCA Pipelining Average:2.171.861.641.48

19. University of Michigan Electrical Engineering and Computer Science 19 Conclusions Expression gap between ISAs and computation ► Inherent inefficiency Transparent ISA Customization ► Fixed core  low NRE ► Plug-and-Play accelerators ► Enables “CISC on demand” 1.8x speedup for 15% area overhead

20. University of Michigan Electrical Engineering and Computer Science 20 Questions? More info: http://cccp.eecs.umich.edu