I seem to be right. The workload was molecular modeling (see blog post); and many of the algorithms are very well suited to GPU, see: http://www.ks.uiuc.edu/Research/gpu/
I am not saying they are newbies for failing to exploit GPUs. There could be other reasons why they did that. For example the pharma needed the results ASAP and may not have ported that particular molecular modeling app to GPU yet. GPGPU is a nascent field after all.
I do too write GPU applications (crypto bruteforcers), just so you know ;)
And I was right. They replied to my comment, saying that workload "still need to be ported [to GPUs]". They just couldn't do it because it was a proprietary app.
I am not saying they are newbies for failing to exploit GPUs. There could be other reasons why they did that. For example the pharma needed the results ASAP and may not have ported that particular molecular modeling app to GPU yet. GPGPU is a nascent field after all.
I do too write GPU applications (crypto bruteforcers), just so you know ;)