DistOS 2014W Lecture 24
The Landscape of Parallel Computing Research: A View from Berkeley
- What sort of applications can you expect to run on distributed OS/parallize?
- How do you scale up
- We can't rely on processor improvements to provide speed-ups
- The proposed computational models that need more processor power don't really apply to regular
- Users would see the advances with games primarily
- More reliance in cloud computing in recent years
7 Dwarfs
- Dense Linear Algebra
- Hard to parallize
- Sparse Linear Algebra
- Spectral Methods
- N-Body Methods
- Structured Grids
- Unstructured Grids
- Monte Carlo
Extended Dwarfs
- Combinational Logic
- Graph Traversal
- Dynamic Programming
- Backtrack/Branch + Bound
- Construct Graphical Models
- Finite State Machines
Features
- Pretty impressive on getting everyone to sign off on the report
- Connection to MapReduce
- Programs that run on distributed operating systems - applications that can be expected to be massively parallel - what sort of computational model is needed - Abstractions needed on top of the stack.
- Predictions about the processing power
- GPU's do have 1000 or more cores
- Desktop cores have not gotten that fast over the past years. They just don't run fast enough.
- Games are the only things that can't be run over the time on single thread
- Low power
- Being able to run a smart phone with 100's of transistors - stalled with the sequential processing
- Why do we need the additional processing power for ? - Games - Games - Games
- Doomsday of the IT industry
- Massive change in mobile and cloud over the past five years
- Linux a very general operating system when it started at first - hard coded to 8086 processor specialized to run on the box. Now it runs everywhere. It has all the abstractions dealing with various aspects of hardware, architecture.