Impressive performance per dollar with CLC Bioinformatics Cell 2.0 from CLC bio

With the release of CLC Bioinformatics Cell 2.0, the world's leading bioinformatics solution provider, CLC bio, raises the bar significantly in terms of performance per dollar in high-performance bioinformatics. Through SIMD technology the Bioinformatics Cell enables users to parallelize calculations on their existing Intel- or AMD-based computers, servers, and clusters - and thereby increase the performance dramatically.

CLC bio's Chief Scientific Officer, Bjarne Knudsen, states, "CLC Bioinformatics Cell accelerates well-known algorithms, such as Smith-Waterman up to 144 times, ClustalW up to 30 times - and in this new version also Sean Eddy's HMMER algorithm up to 37 times. These accelerations are on existing hardware, so scientists don't not need to buy new hardware to get these accelerated algorithms. The speed-up factor varies depending on the processor used, but new multi-core CPUs delivers the best overall performance. However, users will also experience remarkable speed-up factors on hardware that is more than two or three years old, so implementing the Bioinformatics Cell can also be used to effectively prolong a hardware life cycle."

Eliminating the need to purchase additional hardware when opting for a solution including the Bioinformatics Cell, gives users a much more flexible and cost-effective approach to high-performance computing. This means that IT administrators in data centers can prolong the life cycle of their clusters and servers, instead of continually having to stretch the budget to purchase new hardware.

As an example, a 3.0 GHz Pentium 4 can run Smith-Waterman at 0.05 GCUPS (Giga Cell Updates Per Second) with no acceleration, and 3.0 GCUPS with the Bioinformatics Cell implemented. A new 8-core Intel processor can run the same algorithm at 0.31 GCUPS without CLC Bioinformatics Cell - and 44.50 GCUPS with it. A massive 144 times speed-up on the same processor. For a complete benchmark test on four different computer processors, a thorough white paper on the Bioinformatics Cell can be downloaded from the article webpage.