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Field
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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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datasets in scalable GPU-based computing environments. What we provide: A competitive compensation package, with comprehensive health and welfare benefits. A supportive team environment that promotes
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, cybersecurity, software and hardware accelerators such Data Plane Development Kit (DPDK), eBPF, SmartNICs, P4 programmable switches, and GPUs. Situated in USC’s Engineering and Technology Innovation Center
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capabilities. We can access a high-performance computer cluster with the most advanced GPU resources. We also partner with the New York Proton Center, which houses one cyclotron, three rotational gantry
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cluster consisting of 16,616 CPU cores and approximately 100 GPUs, as well as a dedicated AI cluster with 40 A100/H100 GPUs. Position Overview The Department Chair will serve as the academic and
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of the following technology areas: hardware/software co-design, performance optimization with heterogeneous and alternative computing systems (CPU/GPU/NPU/etc.), FPGA design, high-performance computing
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maintenance. Proficiency in programming languages such as Python, R, C#, and SQL. Familiarity with high-performance computing, cloud computing (e.g., AWS), GPUs, and DevOps tools, including version control
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: Experience in real-time simulation hardware like Opal-RT and RTDS. Experience with software development. Experience with use of DSPs, FPGAs, advanced computing (e.g., GPUs, QPUs). Excellent written and oral
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to push the boundaries of what’s possible. We work with petabytes of data, a computing cluster with hundreds of thousands of cores, and a growing GPU cluster containing thousands of high-end GPUs. We don’t
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plasma physics (XGC, IPPL). Expected qualifications: A Master's degree in Computer Science or Applied Mathematics. Necessary knowledge: Modern C++, GPU computing with CUDA/SYCL, MPI, Krylov solvers