1. Parallel Architectures • Why build parallel machines? • To help build even bigger parallel machines • To help solve important problems • Speed – more trials, less time • Cost • Larger problems • Accuracy • Must understand typical problems

2. Introduction • A parallel computer is “a collection of processing elements that communicate and cooperate to solve large problems fast” Speedup(p processors)=performance (p processors)/performance (1 processor) Speedup(p processors)=time(p processors)/time(1 processor)

3. Can run a single parallel application • Speed up the application • Can run multiple independent applications in multiprogramming environment • High throughput • Combination of the two

4. Numeric Symbolic Combinatorial Applications ---> Requirements • Processing • Communication • Memory • I/O • Synchronization • Architect must provide all of the above

5. Requirements ---> Examples • Relaxation - near-neighbor communication • Multigrid - 1, 2, 4, 8, ... communication • Numeric comp - Floating point • Symbolic - Tags, branches • Database - I/O • Data parallel - Barrier synchronicity • Dictionary - Memory, I/O

6. Communication requirements ---> Example • Relaxation • So, let’s build a special machine! • But ... pitfalls!

7. Specialized machines: Pitfalls • Faster algorithms appear … with different communication requirements • Cost effectiveness • Economies of scale • Simpler hardware & software mechanisms • More flexible • May even be faster! • e.g. Specialized support for synchronization across multiple processors