1. CSE 691: Energy-Efficient Computing Lecture 7 SMARTS: custom-made systems Anshul Gandhi 1307, CS building anshul@cs.stonybrook.edu

2. memcache

3. Benchmark competitions

5. fawn paper

6. Data-intensive workloads Seek-bound small random examples? problems? Scan-bound large sequential examples? problems?

7. Why FAWN? 1.Memory wall (??) 2.Increased CPU power consumption 3.DVFS is limited Modern CPUs operate close to V min Constant leakage current 4.Peak power and data center density

8. FAWN results

9. Processor scaling trends 1.Moore’s law (observation) # transistors/chip ↑ 2X/2yr (how?) Frequency ↑ as transistor size ↓ (max 9GHz) Leakage current/power ↑ as transistor size ↓ Heat ↑ as frequency ↑

10. Processor scaling trends 2.Dennard scaling (observation) Transistor power (V+I) ↓ as transistor size ↓ + Moore’s law = perf/watt ↑ 2X/2yr (how?) Not true now due to leakage current So we did multicore!

11. heteromates paper

12. Dark silicon Cannot power on all of the CPU Result of: 1.Success of Moore’s law 2.Failure of Dennard scaling Turbo boost

13. Main ideas Heterogeneous cores 1.For different performance requirements 2.Energy considerations (battery vs. plugged) 3.Thermal considerations 4.Dark silicon

14. Main ideas