[Beowulf] Berkeley View: A future in Parallel Programming?

Thomas H Dr Pierce TPierce at rohmhaas.com
Thu Mar 15 05:44:46 PDT 2007

Dear Beowulf ML,

Here is an interesting discussion on the methods and metrics that could 
apply to multicore chips and clusters. 

I have not seen this discussed on the list, so it may be new to some.

Here is the link to the overview wiki

And motivation for people to go to the link: quote from the wiki
"We believe that much can be learned by examining the success of 
parallelism at the extremes of the computing spectrum, namely embedded 
computing and high performance computing. This led us to frame the 
parallel landscape with seven question under the following assumptions: 
The target should be 1000s of cores per chip, as this hardware is the most 
efficient in MIPS per watt, MIPS per area of silicon, and MIPS per 
development dollar. 
Instead of traditional benchmarks, use 7+ ?dwarfs? to design and evaluate 
parallel programming models and architectures. (A dwarf is an algorithmic 
method that captures a pattern of computation and communication.) 
?Autotuners? should play a larger role than conventional compilers in 
translating parallel programs. 
To maximize programmer productivity, programming models should be 
independent of the number of processors. 
To maximize application efficiency, programming models should support a 
wide range of data types and successful models of parallelism: data-level 
parallelism, independent task parallelism, and instruction-level 
parallelism. "

And the detailed white paper that  started his (Dec 2006) 

The "Seven Questions" discuss approaches to what seem to be standard 
discussions on cluster, parallel programming and best practices.  Lots of 
fun for everyone! 


1. What are the applications? 
2. What are common kernels of the applications? 

Architecture and Hardware 

3. What are the HW building blocks? 
4. How to connect them? 

Programming Model and Systems Software 

5. How to describe applications and kernels? 
6. How to program the hardware? 


7. How to measure success? 


   Tom Pierce
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