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Genetics is normally very very data parallel. And often the ideal case for throughput computing. But there are rare times when doing modelling that a lot of cha
by jerven 13y ago
Genetics is normally very very data parallel. And often the ideal case for throughput computing. But there are rare times when doing modelling that a lot of chatter is required over interconnects. But even here people normally just get 4-6TB RAM machines instead of having lots of machines.
- dekhn 13y agoyes, and the people buying those machines often tell me that their science is limited by how much RAM they could buy in a single machine. Which is poppycock.
- jerven 13y agoOh, you could make this run using MPI etc... no problem. But then all you are really doing is going from high density to low density ram. And that is just not as large a saving as you would think it is. Because you are expanding rapidly the number of cpu's and racks you need to compensate for the less dense RAM. A good sequencing lab does not need more RAM than that per assembly. If you have a reference even less. Plus the science is hard enough that throwing mulitnode programming in the middle is tricky. Remember most of this code is written by a PhD student on his first real programming job. Its hard enough to go from getting it to run on something else than the PhD students laptop, never mind robustly parallelize this across nodes.