Computing at Scale: Challenges & Opportunities

I was watching the video, Computing at Scale: Challenges & Opportunities, a panel at Google Faculty Summit. Here are few interesting points made.

They observe few trends/problems (ones caught my ears, not comprehensive)

1. We are drowning in data - Data Intensive Computing, How to handle lot of Data (e.g. Telescope could generate 200GB/sec).
   
2. Data Driven approach is becoming popular
   
3. How to Program large scale systems? Patterns, Middleware and teaching students to programme using them?
4. Storage and Computing power is becoming Cheaper, and they are going to be placed remotely.
   
5. Need for multidisciplinary collaborations to solve problems (e.g. e-science problems)
   

Few observations

1. With cloud cost of 1000 cpus per day = 1 cpu for 1000 days - Prof Patterson's observation
2. In large scale systems, no matter high reliable, H/W fails, and S/W has to handle it - observation at Google
3. Animoto (Company running on EC2), was using about 50 nodes, but due to a face book app they had to handle 10X user base with in a week, and they were able to bump up their system to 3500 nodes using EC2. See here for details.