2. CIS429.S00: Lec2- 1 Performance Overview Execution time is the best measure of performance: simple, intuitive, straightforward. Two important quantitative methods : –Amdahl’s Law and Speedup –CPI - cycles per instruction Benchmarks Metrics for summarizing performance data Pitfalls

3. CIS429.S00: Lec2- 2 Time-based Metrics Elapsed time to run the task –Execution time, response time, latency Rate: tasks completed per day, hour, week, sec, ns –Throughput, bandwidth Plane Boeing 747 Concorde Speed 610 mph 1350 mph DC to Paris 6.5 hours 3 hours Passengers 470 132 Throughput 286,700 178,200 In passenger-mile/hour

4. CIS429.S00: Lec2- 3 Performance comparisons "X is n times faster than Y" means ExTime(Y) Performance(X) --------- = --------------- = n ExTime(X) Performance(Y)

5. CIS429.S00: Lec2- 4 Execution time metric wall clock time = response time = elapsed time CPU time = user CPU time + system CPU time We will measure CPU performance using user CPU time on an unloaded system Example: Unix time command 90.7u 12.9s 2:39 65%

6. CIS429.S00: Lec2- 5 Amdahl's Law Speedup due to enhancement E: ExTime w/o E Performance w/ E Speedup(E) = ------------- = ------------------- ExTime w/ E Performance w/o E Suppose that enhancement E accelerates a fraction F of the task by a factor S, and the remainder of the task is unaffected

7. CIS429.S00: Lec2- 6 Amdahl’s Law ExTime new = ExTime old x (1 - Fraction enhanced ) + Fraction enhanced Speedup overall = ExTime old ExTime new Speedup enhanced = 1 (1 - Fraction enhanced ) + Fraction enhanced Speedup enhanced

8. CIS429.S00: Lec2- 7 Amdahl’s Law Floating point instructions improved to run 2X; but only 10% of actual instructions are FP Speedup overall = 1 0.95 =1.053 ExTime new = ExTime old x (0.9 +.1/2) = 0.95 x ExTime old Corollary: Make the common case fast!

9. CIS429.S00: Lec2- 8 Amdahl’s Law Corollary: Make the common case fast! All instructions require instruction fetch, only a fraction require data fetch/store. ==> optimize instruction access over data access Access to small memories is faster. ==> organize the storage hierarchy such that most frequent accesses are to the smallest/closest memory unit. Programs exhibit locality (spatial and temporal). ==> implement pre-fetching of nearby code/data