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hardware architectures (multicore, GPUs, FPGAs, and distributed machines). In order to have the best performance (fastest execution) for a given Tiramisu program, many code optimizations should be applied
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the Computer Science program at New York University Abu Dhabi, seeks to recruit a research assistant to work on the intersection of compilers and deep learning. Many companies, such as Google, Facebook, and Amazon
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(fastest execution) for a given Tiramisu program, many code optimizations should be applied. Optimizations include vectorization (using hardware vector instructions), parallelization (running loop iterations
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computers (e.g., parallelizing and distributing code). Experience in distributed data management and workflow systems. Preferred Competencies Ability to build systems where agents operate with independence
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the Computer Science program at New York University Abu Dhabi, seeks to recruit a research assistant to work on the intersection of compilers and deep learning. Many companies, such as Google, Facebook, and Amazon
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programming; Experience programming distributed systems; Experience with parallel and distributed File Systems (e.g., Lustre, GPFS, Ceph) development. Advanced experience with high-performance computing and/or
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. Demonstrated experience developing and running computational tools for high-performance computing environment, including distributed parallelism for GPUs. Demonstrated experience in common scientific programming
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programming; Experience programming distributed systems; Experience with parallel and distributed File Systems (e.g., Lustre, GPFS, Ceph) development. Advanced experience with high-performance computing and/or
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) for a given Tiramisu program, many code optimizations should be applied. Optimizations include vectorization (using hardware vector instructions), parallelization (running loop iterations in parallel
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programming; Experience programming distributed systems; Experience with parallel and distributed File Systems (e.g., Lustre, GPFS, Ceph) development. Advanced experience with high-performance computing and/or