Difference between revisions of "MapReduce, Globus, BOINC"
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*The type of problems that we most care about tend not to be THAT parallel | *The type of problems that we most care about tend not to be THAT parallel | ||
*So what would a | *So what would a distributed OS be for? | ||
**Shared communication! | **Shared communication! | ||
***But we don't have much in the way that works well. | ***But we don't have much in the way that works well. | ||
*An OS typically provides a lot of services, together in one package | *An OS typically provides a lot of services, together in one package | ||
**We have been seeing that there are no complete packages, just pieces and parts. Why? | **We have been seeing that there are no complete packages, just pieces and parts. Why? | ||
***Computers are changing too fast? Same *NIX OS, same | ***Computers are changing too fast? Same *NIX OS, same TCP/IP stack... so more of the same, why no true solution? | ||
***Communication is unreliable? Yes, but that is also nothing new | ***Communication is unreliable? Yes, but that is also nothing new | ||
*If people found that distributed file systems were | *If people found that distributed file systems were successful, they would be in use all the time, but they aren't. Reason? PERFORMANCE | ||
*Take away message? | *Take away message? | ||
*Can't handle communication - how do you abstract access to resources when driven through a network? | *Can't handle communication - how do you abstract access to resources when driven through a network? | ||
**As a result, we have many many | **As a result, we have many many specialized solutions for particular workloads. | ||
*If you are willing to not have communication between nodes, you gain a HUGE amount of computation | *If you are willing to not have communication between nodes, you gain a HUGE amount of computation. | ||
*The most reliable systems are the one that forget communication. | |||
Revision as of 15:14, 26 March 2008
Readings
Ian Foster and Carl Kesselman, "Computational Grids" (1998)
Ian Foster, "Globus Toolkit Version 4: Software for Service-Oriented Systems" (2006)
David P. Anderson, "BOINC: A System for Public-Resource Computing and Storage" (2004)
Jeffrey Dean and Sanjay Ghemawat, "MapReduce: Simplified Data Processing on Large Clusters" (2004)
Notes
BOINC
- Premise? Local client on your machine downloads a 'workunit', churns the data, dumps the results and downloads a new 'workunit'
- Why are we caring?
- Entertainment?
- How is this an OS paradigm? What is it useful for?
- It isn't really an OS, just a method to have your mass computation done
- More of a distributed scheduler?
- Not even, central scheduler, but mass computation
- How many systems have we seen that have accomplished mass computation on millions of uncontrolled computers?
- ummm... none?
- As an OS?
- An OS is something that is created to run programs
- This is a special case allowing us to run specific programs (BUT IS IT AN OS?)
- Useful for "embarassingly parallel programs"
- Perfect for large scale simulation?
- But then you need LOTS of communication, and this system does not have interconnects
- The type of problems that we most care about tend not to be THAT parallel
- So what would a distributed OS be for?
- Shared communication!
- But we don't have much in the way that works well.
- Shared communication!
- An OS typically provides a lot of services, together in one package
- We have been seeing that there are no complete packages, just pieces and parts. Why?
- Computers are changing too fast? Same *NIX OS, same TCP/IP stack... so more of the same, why no true solution?
- Communication is unreliable? Yes, but that is also nothing new
- We have been seeing that there are no complete packages, just pieces and parts. Why?
- If people found that distributed file systems were successful, they would be in use all the time, but they aren't. Reason? PERFORMANCE
- Take away message?
- Can't handle communication - how do you abstract access to resources when driven through a network?
- As a result, we have many many specialized solutions for particular workloads.
- If you are willing to not have communication between nodes, you gain a HUGE amount of computation.
- The most reliable systems are the one that forget communication.