1. University of Michigan Electrical Engineering and Computer Science Dynamic Voltage/Frequency Scaling in Loop Accelerators using BLADES Ganesh Dasika 1, Shidhartha Das 2, Kevin Fan 1, Scott Mahlke 1, David Bull 2 1 1 University of Michigan Advanced Computer Architecture Laboratoy Ann Arbor, MI 2 ARM Ltd. Cambridge United Kingdom

2. University of Michigan Electrical Engineering and Computer Science Introduction 2 [Austin, IEEE Computer March 04]

3. University of Michigan Electrical Engineering and Computer Science Razor Allows for voltage/frequency scaling beyond first-failure point Exploits difference between design-time conditions (“slow”) and actual conditions (“typical”) 3 [Das, JSSC 2006]

4. University of Michigan Electrical Engineering and Computer Science Razor in General Purpose Processors Requires detailed analysis of microarchitectural impact –Analyze what state should be stored –Lengthening pipeline for stabilization increases complexity of forwarding logic Unpredictable control and data flow Difficult to determine worst-case vectors 4

5. University of Michigan Electrical Engineering and Computer Science BLADES Better-than-worst-case Loop Accelerator Design Incorporate DVFS into ASICs using Razor –Shave off some of the high NRE using HLS –Develop generic methodology for any application –Razor solution for a templated architecture Create ASIC design flow that is aware of Razor-ization costs 5

6. University of Michigan Electrical Engineering and Computer Science Loop Accelerator Template Hardware realization of modulo-scheduled loop Parameterized execution resources, storage, connectivity Control is statically determined, simple and not timing-critical Opportunity to make application-specific optimizations 6

7. University of Michigan Electrical Engineering and Computer Science Razorized Loop Accelerator 7 Razor + + * * + + * * Extended register queues Added interconnect “Roll-back” muxes } R R is the number of extra entries required Function of max pipeline depth and error-detection delay

8. University of Michigan Electrical Engineering and Computer Science Error “Life-Cycle” 8 Razor + + * * + + * * Error Reset Error … Error OR-tree Error stabilization Roll-back pipelining … + + Error processing Control

9. University of Michigan Electrical Engineering and Computer Science Issues with Razor Area, added hold-fixing 9 t spec D CLK

10. University of Michigan Electrical Engineering and Computer Science 10 Or1 Or0 FU 1 Add1 Add0 FU 0 Time 5Time 4Time 3Time 2Time 1Time 0 Or1FU 3 Or0FU 2 Add1FU 1 Add0FU 0 Time 2Time 1Time 0 Add-Or1Add-Or0FU 0 Time 3Time 2Time 1Time 0 Or1Or0FU 1 Add1Add0FU 0 Time 2Time 1Time 0 50% FU utilization removes hold-fixing need, but requires halving performance or doubling area Use hybrid scheme to execute >2 ops per FU + + I I Opcode-chaining

11. University of Michigan Electrical Engineering and Computer Science Identifying Opcode Chains Compiler identifies subgraphs of 3-4 input, 1 output instructions –All arith. ops supported Greedy selection algorithm 11 << + + + + >> + + + + + + + + + & & ST & & >> + + << + + LD >> LD 1 2 3 4 5 6 7

12. University of Michigan Electrical Engineering and Computer Science Custom FUs 12 << + + + + >> + + + + + + + + + & & ST & & >> + + << + + LD >> LD 1 2 3 4 5 6 7 << + + + + >> + + + + + + + + + & & ST & & >> + + << + + LD >> LD 1 2 3 4 5 6 7 >> + + << + Enabled every 2 cycles Razor DFF

13. University of Michigan Electrical Engineering and Computer Science Results 13 idct, sharp, systolic_dct had multiple CFUs, and overall lower # of FUs Viterbi, dequant had signficant control-flow that restricted opportunities for creating custom ops 22% reduction in hold-fixing overhead in sobel

14. University of Michigan Electrical Engineering and Computer Science Conclusion Application-specific optimizations definitely help to mitigate Razor costs –24% reduction in overhead –33% energy savings overall Can optimize Razor-ization with further input from the compiler –Critical-instruction analysis –Error impact analysis 14

15. University of Michigan Electrical Engineering and Computer Science Thank you! 15 http://cccp.eecs.umich.edu

16. University of Michigan Electrical Engineering and Computer Science Future Work Errors in different FUs affect the system differently –Error “impact-analysis” –Data computation not necessarily error-sensitive –Address, branch target/direction critical to functionality Razor-ization of arbitrary Verilog 16

17. University of Michigan Electrical Engineering and Computer Science Motivation Using Razor has significant design overhead –Error-recovery system –Added “backup” state –Additional hold-time fixing Modifications for different u-archs are different Information about work-load cannot be used since design must preserve generality 17

18. University of Michigan Electrical Engineering and Computer Science 18 + + * *