Parallel algorithm

The genome of an organism can be expresses as some number G of

"base pairs" (see http://en.wikipedia.org/wiki/Base_pair). Typical

sizes of various genomes are given in (http://en.wikipedia.org/wiki/Genome).



String matching can be used to find particular sequences in a

genome. Several string matching algorithms are described

in (http://en.wikipedia.org/wiki/String_matching)



Consider a program to find to find if a particular sequence of

base pairs is found in a genome, and if so, where and how

many times.



Your program will run on a cluster with 

the following properties:



Number of nodes - 20



  Number of processors per node 16 2.6 GHz Xeon

  Memory per node               16 GB

  GPU - 2 (NVIDIA CUDA) per node, 1024 stream processors and 4GB RAM, running at 1.5 GHz 

  local drives 1 T SATA , 6 GB/sec

  NFS drive 10TB  RAID, bandwidth limited by network

                

Switched Ethernet network

Latency               L = 20 microseconds

Bandwidth             B = 1Gb/sec == 100 Mbytes/sec for messages

   larger than 32Kbytes





You may not need all the above information. If you feel you need some other system 

property, feel free to assume some reasonable value (Try Wikipedia)



Assume the genome you are exploring and the sequence you are

trying to find, are both initially files on the NFS disk.



Deliverables:



1. Parallel String Match algorithm - in MPI, OpenMP, CUDA or some

combination of these. Description in English and/or pseudocode is

sufficient. Is yoyur algorithm data parallel, task parallel or both? 



Describe data transfer during computation (disk to program, process to process,

CPU - GPU and node - node). Describe how data is partitioned between processes, 

shared between processes, or replicated at each process.



2. You may not need all the hardware available for your algorithm. You may use the

entire cluster or any part of it. Describe what resources your algorithm will use to 

execute. Explain your choice.



3. Estimate how your algorithm would perform on the computer

system described above. Consider:

    a. Complexity; communication costs.

    b. Is there some file size (in bytes, number of elements, or both)

that is too small for your algorithm to work efficiently? Given the wide range of genome

sizes (see http://en.wikipedia.org/wiki/Genome), is there some range of size that you expect would

be best for your algorithm?

    c. How much speedup would you exepect on the given hardware as compared to running

on a single CPU? Justify your answer

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