1. Future of parallel computing: issues and directions Laxmikant Kale CS433 Spring 2000

2. At the crossroads Sequential computers are much faster than they were: –Question: is that adequate for most applications? Bimodal distribution of applications –Are there new applications needing more power? –Are they economically important? Likely answer: need parallel machines, but.. –Software crisis?

3. Performance challenges: Latency tolerance Scalability: –Can we utilize 10,000 processors on one problem? 10,000 PE machines (almost) already here (9k). 100,000? Million? Increasing gap between processor and memory performance –Probably the most challenging issue today

4. Processors in Memory PIM, or also, intelligent RAM (IRAM) Idea: embed processors in memory, SRAM? DRAM? Read IRAM paper by Patterson et al. –IEEE Macro, April 1997. Will be on the course web page

5. Explicit management of caches Explicit management: –Let the user program decide what stays in cache and when –Instructions for data movement –Problem: limited buffer –Solution: handle overflow in software? –Let compilers be smart enough to use this control –Notice: data-driven objects have an advantage here as well: schedulers can prefetch relevant data in cache