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Field
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management, cache optimization, and vectorization techniques. Strong understanding of algorithms and data structures, especially those suitable for parallel processing and distributed computing. Understanding
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for scientific computing to support users in the process of solving increasingly complex compute- and data-intensive problems in science and engineering on high-end parallel and distributed computing platforms
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management, cache optimization, and vectorization techniques. Strong understanding of algorithms and data structures, especially those suitable for parallel processing and distributed computing. Understanding
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increasingly complex compute- and data-intensive problems in science and engineering on high-end parallel and distributed computing platforms. The selected candidate will play an integral part in the group's
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the process of solving increasingly complex compute- and data-intensive problems in science and engineering on high-end parallel and distributed computing platforms. The selected candidate will play an integral
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 3 months ago
, valgrind, etc.); solid experience with performance measurements, application profiling, and performance analysis. Must have strong knowledge in Parallel Programming and Distributed Computing. Being familiar
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and run-time management of parallel and distributed computer systems. The modeling, analysis and optimization of the extra-functional aspects of these systems, such as performance, power/energy
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Science or a closely related field. • You have experience in matrix algorithms, data compression, parallel computing, optimization of advanced applications on parallel and distributed systems. • An excellent
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State University of New York University at Albany | Albany, New York | United States | about 24 hours ago
vibration isolation). In parallel to the benefits of quantum computing, artificial intelligence and neuromorphic computing seek to emulate the massively parallel, highly efficient computing capacity
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fundamentals and hands-on experience with HPC systems; parallel/distributed programming and/or solid UNIX skills Proven experience operating Machine Learning (ML) in production. Able to design, automate, and