High-performance computing (HPC) is in a state of transition. HPC users have traditionally relied upon two things to supply them with processing power: speed of the central processing units (CPUs) and the scalability of the system. There are problems with this approach. Physical limitations are curtailing clock speed increases in general-purpose CPUs, the von Neumann load-execute-store approach does not map well to every computational problem, and systems of thousands of ...
Reconfigurable computing refers to computations done with flexible fabrics where the data path and control flow can be customized to the application. Unlike traditional computing using the fetch, execute, and store model that is highly sequential, reconfigurable computing allows developers to program their applications both spatially and temporally. This allows for potentially great speed-ups with applications that might be well-suited for such approaches. However, programming in this style requires specialized ...
Computational science applications and advanced scientific computing have made tremendous gains in the past decade. Researchers are regularly employing the power of large computing systems and parallel processing to tackle larger and more complex problems in all of the physical sciences. For the past decade or so, most of this growth in computing power has been "free" with increased efficiency more-or-less governed by Moore's Law. However, increases in performance are ...
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