Lecture 1: Introduction

1. Lecture 1:Introduction

2. Performance Evaluation of Computer Systems Computer systems consist of: • Processor • Memory • Input/Output • Operating system • Network Memory instruction data Input unit Output unit Processor P P P P Network

3. Performance Evaluation of Computer Systems Performance depends on: • Technology • Instruction Set Architecture • Organization • Software

4. Technology • In recent years, microprocessors have become smaller and denser.

5. Technology

6. Moore’s Law • Gordon Moore predicted in 1965 that the transistor density of semiconductor chips would double roughly every18 months.

7. Moore’s Law • Number of transistors • Performance Double every 1.5 year.

8. Top500 List at June 2013

9. Performance Units Speed 1 Mflop/s 1 Megaflop/s 106 Flop/second 1 Gflop/s 1 Gigaflop/s 109 Flop/second 1 Tflop/s 1 Teraflop/s 1012 Flop/second 1 Pflop/s 1 Petaflop/s 1015 Flop/second 1 Eflop/s 1 Exaflop/s 1018 Flop/second Storage 1 MB 1 Megabyte 106 Bytes 1 GB 1 Gigabyte 109 Bytes 1 TB 1 Terabyte 1012 Bytes 1 PB 1 Petabyte 1015 Bytes

10. Moore’s Law Limits of Moore’s Law: • Moore’s Law is exponential. Exponentials can not last forever. • The size of atoms is the fundamental barrier • Heat is a problem in today’s CPUs

11. Moore’s Law Reinterpreted • Number of cores per chip doubles every 2 years • Multicore architectures

12. Moore’s Law Reinterpreted • Number of cores per chip doubles every 2 years, while clock speed decreases • Multicore architectures

13. Performance Evaluation of Computer Systems Performance depends on: • Technology • Instruction Set Architecture • Organization • Software

14. Instruction Set Architecture-ISA Instruction Set Design: • RISC / CISC • Code density • Number of operands • Stack machines (0-operand) • Accumulator machines (1-operand) • Register machines (2-operand, 3-operand)

15. Performance Evaluation of Computer Systems Performance depends on: • Technology • Instruction Set Architecture • Organization • Software

16. Organization Memory Hierarchy CPU Registers L1 Cache L2 Cache Main Memory Disk Tape

17. Organization Manycore Chips Single-core Dual-core CPU CPU CPU Registers Registers Registers L1 Cache L1 Cache L1 Cache L2 Cache L2 Cache Main Memory Main Memory

18. Performance Evaluation of Computer Systems Performance depends on: • Technology • Instruction Set Architecture • Organization • Software

19. Course Outline The aim of this course: • Introduction to the methods and techniques of performance analysis of computer systems. • Solve computer performance analysis problems related to • measuring performance of computer systems, • planning the capacity, • predicting the future performance under different configurations, • designing new applications that meet performance requirements, • comparison of computer systems • Hands-on experiments on modern hardware/software systems

20. Course Outline • Introduction • Hardware and software aspects of computer systems • Performance metrics • Performance measurement tools and techniques • Benchmarking • Statistical analysis of performance experiments • Design of experiments • Processor Performance • ALU • Pipelining • Optimizing program performance • Memory Hierarchy • Cache performance • Optimizing program performance • Performance of multiprocessor systems • Simulation • Queueing Theory

21. Course Outline Textbook: • D. Lilja, “Measuring Computer Performance: A Practitioner's Guide”, Cambridge University Press Reference Books: • P.J. Fortier, H.E. Michel, “Computer Systems Performance Evaluation and Prediction”, Digital Press • K.R. Wadleigh, I.L. Crawford, “Software Optimization for High Performance Computing”, Prentice-Hall • Computer Systems: A Programmer’s Perspective, R.E. Bryant, D.R.O’Hallaron, Pearson • Computer Architecture, J.L. Hennessy, D.A. Patterson, Morgan & Kaufmann • High Performance Computing, K.R. Wadleigh, I.L. Crawford, Prentice Hall

22. Course Outline Grading: • Assignments 30% • Midterm 30% • Final Exam 40%