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Next-generation, high-throughput sequencers are now capable of producing hundreds of billions of short sequences (reads) in a single day. The task of accurately mapping the reads back to a reference genome is of particular importance because it is used in several other biological applications, e.g., genome re-sequencing, DNA methylation, and ChiP sequencing. On a personal computer (PC), the computationally...
The graphics processing unit (GPU) has evolved from being a fixed-function processor with programmable stages into a programmable processor with many fixed-function components that deliver massive parallelism. By modifying the GPU's stream processor to support “general-purpose computation” on the GPU (GPGPU), applications that perform massive vector operations can realize many orders-of-magnitude...
While GPGPU stands for general-purpose computation on graphics processing units, the lack of explicit support for inter-block communication on the GPU arguably hampers its broader adoption as a general-purpose computing device. Interblock communication on the GPU occurs via global memory and then requires barrier synchronization across the blocks, i.e., inter-block GPU communication via barrier synchronization...
Through the algorithmic design patterns of data parallelism and task parallelism, the graphics processing unit (GPU) offers the potential to vastly accelerate discovery and innovation across a multitude of disciplines. For example, the exponential growth in data volume now presents an obstacle for high-throughput data mining in fields such as neuroscience and bioinformatics. As such, we present a...
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