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Datorteknik PerformanceAnalyse bild 1 Performance –what is it: measures of performance The CPU Performance Equation: –Execution time as the measure –what affects execution time –examples Choosing good benchmarks? –choosing bad benchmarks? Amdahl's Law
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Datorteknik PerformanceAnalyse bild 2 Performance is Time Time to do the task (Execution Time) –execution time, response time, latency Tasks per unit time (sec, minute,...) –throughput, bandwidth
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Datorteknik PerformanceAnalyse bild 3 Performance as Response Time Performance is most often measured as response time or execution time for some task. “X is n times faster than Y” means Performance(X) Execution Time(Y) –––––––––––––– = –––––––––––––––– = n Performance(Y) Execution Time(X) Example Execution time of program P X is 5 sec; Y is 10 sec. X is 2 times faster than Y.
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Datorteknik PerformanceAnalyse bild 4 What time to measure? Elapsed time, wall-clock time: –actual time from start to completion –depends on CPU, system, I/O, etc. –often used in real benchmarks –only suitable choice when I/O is included CPU Time: –measure/analyze CPU performance only –may be suitable when machine is timeshared –possibly both user and system component –User CPU time is our focus for first part of course Elapsed time = CPU time + Idle time –usually and assuming time is accurately accounted for
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Datorteknik PerformanceAnalyse bild 5 Metrics of performance Different performance metrics are appropriate at different levels: Compiler Language Programming Application Datapath Control Function Units Transistors ISA Answers per month Operations per second (millions) of Instructions per second – MIPS (millions) of (F.P.) operations per second – MFLOP/s Cycles per second (clock rate) Cycles per Instruction
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Datorteknik PerformanceAnalyse bild 6 Relating Processor Metrics CPU execution time per program = CPU clock cycles/program X Clock cycle time = CPU clock cycles/program ÷ Clock rate (frequency) CPU clock cycles/program = Instructions/program X Clock cycles Per Instruction Clock cycles Per Instruction (CPI) is an average measurement, it depends on : –ISA, the implementation, and the program measured –CPI = CPU clock cycles/program ÷ Instructions/program –Also, Instructions per clock cycle or IPC = 1 / CPI CPU execution time = Instructions X CPI X Clock cycle
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Datorteknik PerformanceAnalyse bild 7 Let’s look at the single-cycle model analytically
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Datorteknik PerformanceAnalyse bild 8 Static timing analysis Memories10 ns Register 5 ns Adders10 ns ALU10 ns Use topological sort!
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Datorteknik PerformanceAnalyse bild 9 5 ns Branch logic Sgn/Ze extend Zero ext. lw $2 const($3) 10 ns ALU A B 31 0 4 + + 10 ns 35 ns delay
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Datorteknik PerformanceAnalyse bild 10 But that path goes through the data memory! What if this is not a load/store? How about an instruction that does nothing? “NOP”
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Datorteknik PerformanceAnalyse bild 11 5 ns Branch logic Sgn/Ze extend Zero ext. Nop 10 ns ALU A B 31 0 4 + + 10 ns 10 ns delay
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Datorteknik PerformanceAnalyse bild 12 5 ns Branch logic Sgn/Ze extend Zero ext. Add $ra $rb $rc 10 ns ALU A B 31 0 4 + + 10 ns 25 ns delay
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Datorteknik PerformanceAnalyse bild 13 5 ns Branch logic Sgn/Ze extend Zero ext. B label 10 ns ALU A B 31 0 4 + + 10 ns 20 ns delay
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Datorteknik PerformanceAnalyse bild 14 35 ns for load/store but 10 ns for NOP !?
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Datorteknik PerformanceAnalyse bild 15 Amdahl’s rule: “Make the common case fast”
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Datorteknik PerformanceAnalyse bild 16 Amdahl's Law Handy for evaluating impact of a change not tied to CPU performance equation Insight: No improvement of a feature enhances performance by more than the use of the feature. Suppose that enhancement E accelerates fraction F of a program by a factor S (remainder of the task is unaffected): ExecTime E = ((1 – F( + (F/S)) X ExecTime without F1-F E S = F/S
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Datorteknik PerformanceAnalyse bild 17 What if we don’t need the ALU? A branch instruction?
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Datorteknik PerformanceAnalyse bild 18 BUT! The single cycle model has to accomodate the slowest instruction Even if it rarely occurs!
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Datorteknik PerformanceAnalyse bild 19 How much work can our structure perform? For a program Q: Time = Number of executed instruction * Number of cycles per instruction * Time per cycle T = Nq * CPI * Tc
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Datorteknik PerformanceAnalyse bild 20 For the single cycle model.... CPI = 1 for all instructions Tc determined by the slowest instruction
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Datorteknik PerformanceAnalyse bild 21 How to reduce T? T = Nq * CPI * Tc Reduce Nq. More powerful instructions! More hardware, longer paths, cycle time goes up (slower machine)
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Datorteknik PerformanceAnalyse bild 22 “No free lunch” Why designers are so well paid - to optimize designs.
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Datorteknik PerformanceAnalyse bild 23 How to reduce T? T = Nq * CPI * Tc Faster hardware Technological limits Cost increase not linearly related Sales volume drops
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Datorteknik PerformanceAnalyse bild 24 How to reduce T? T = Nq * CPI * Tc Make this a function of the instruction For example:NOP = 1 cycle LW = 4 cycles Chapter 5.4, the classical method
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Datorteknik PerformanceAnalyse bild 25 How to reduce T? T = Nq * CPI * Tc Make this a function of the instruction CPI goes up, but we can use an average, not the worst case Tc goes down, time to do the longes step, not the entire instruction
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Datorteknik PerformanceAnalyse bild 26 Example Branch:Step 1: fetch Step 2: New PC Add:Step 1: fetch Step 2: decode/ register fetch Step 3: Compute and write back
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Datorteknik PerformanceAnalyse bild 27 Example LW = 4 steps Cycletime = 1/4 old time T = 4 * 1/4 old time, LW CPI just as slow for the lw instruction our worst case!
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Datorteknik PerformanceAnalyse bild 28 But that’s not important if LW is not common! T = Nq * CPI * 1/4 old time Averaged over this many instructions 1,3? 1,7? Never = 4,0!
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Datorteknik PerformanceAnalyse bild 29 We win because of quantitative statistical properties of our programs!
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Datorteknik PerformanceAnalyse bild 30 What value of CPI do we use? 1,3?1,5?1,7? Easy: Use average program! ?
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Datorteknik PerformanceAnalyse bild 31 There is no such thing!
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Datorteknik PerformanceAnalyse bild 32 Artificial “average programs” called “benchmarks” Are they something to trust? What about “peak performance values” mips?mflops? We have a peak at CPI = 1.......a program of only NO-OPS!
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Datorteknik PerformanceAnalyse bild 33 Why Do Benchmarks ? How we evaluate performance differences –Across and within a single system (design & variations) What should benchmarks do? –Represent a large class of important programs –Behave like typical programs: improved benchmark performance => improved performance broadly For better or worse, benchmarks shape a field Good ones accelerate progress Bad benchmarks hurt progress –help real programs vs. sell machines/papers? –Enhancements that help benchmarks may not help most programs and v.v.
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Datorteknik PerformanceAnalyse bild 34 Classes of Benchmarks (Toy) Benchmarks –10-100 line–e.g.,: sieve, puzzle, quicksort –good first programming assignments Synthetic Benchmarks –attempt to match average frequencies of real workloads –e.g., Whetstone, dhrystone –mostly good for nothing: too artificial Kernels –Time critical excerpts of real programs –e.g., Livermore loops, Linpack –good for micro-performance studies Real programs –e.g., gcc, spice, Verilog, Database, stock trading
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Datorteknik PerformanceAnalyse bild 35 Successful Benchmark: SPEC Collection 1987 RISC industry (workstations) mired in “bench marketing”: –(“That is an 8 MIPS machine, but they claim 10 MIPS!”) EE Times + 5 companies band together to perform Systems Performance Evaluation Committee (SPEC) in 1988: –Sun, MIPS, HP, Apollo, DEC Create standard list of programs, inputs, reporting rules: –several real programs, including OS calls –some I/O –rules for running and reporting
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Datorteknik PerformanceAnalyse bild 36 Multiple clock cycle designs: State machines Micro programming chapter 5.4 “VLSI” design
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Datorteknik PerformanceAnalyse bild 37 How to reduce T? T = Nq * CPI * Tc Reduce quotient cycles / instruction reduce “cycles”multiple clock- cycle design Increase “instruction”execute more than one instr. per cycle!
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Datorteknik PerformanceAnalyse bild 38 More than one instruction per cycle? Parallelism –Div/mult + floating point + integer Superscalarity –Multiple issue etc. Pipelining –Of general importance
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