Nakul Jindal

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Performance modeling is becoming an increasingly important part of the parallel application development process, particularly for expensive computations that will be run on very high-end systems where resources are scarce. We describe a performance modeling tool SIPMaP (Super Instruction Processor Modeling and Prediction) developed for the Super-Instruction(More)
The Super Instruction Architecture (SIA) is a parallel programming environment designed for problems in computational chemistry involving complicated expressions defined in terms of tensors. Tensors are represented by multidimensional arrays which are typically very large. The SIA consists of a domain specific programming language, Super Instruction(More)
Aces4 is a parallel programming platform comprising a DSL for Computational Chemistry and its runtime system. It offers a convenient way to express parallelism together with extensive support for extremely large, possibly sparse, distributed arrays. It aids scientists in the creation of performant, scalable, massively parallel programs that can effectively(More)
In scientific computing, scaling issues frequently occur as more processors are utilized and/or the problem size is increased. Applications that run well on small problems and small machines, don't necessarily work well, or at all when executed at larger scale. It is desirable to avoid using expensive supercomputer time for discovering and correcting(More)
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