Doctoral Dissertation Defense: Samuel Khuvis
Advisor: Dr. Gobbert
Location
Mathematics/Psychology : 401
Date & Time
January 29, 2016, 1:00 pm – 2:00 pm
Description
Title: Porting and Tuning Numerical Kernels in Real-World Applications to Many-Core Intel Xeon Phi Accelerators
Abstract: Modern architectures with multiple memory hierarchies in multi-core CPUs and coprocessors such as the massively parallel GPGPU and many-core Intel Xeon Phi offer opportunities to drastically speed up numerical kernels. Coprocessors, which supplement the work of the CPUs, generally have significantly more cores and threads than a multi-core CPU and use power more efficiently. The Intel Xeon Phi is a newer hardware released to the public only in 2013. Three modes of execution are available on the Intel Phi: (i) offloading, where the program is run on the CPU and segments of the code are moved to the Intel Phi, similar to GPGPU programming, (ii) native, where the program is run directly on the Intel Phi, and (iii) symmetric, where the program is run on the CPU and Phi jointly. We report the performance of three test problems whose structure is representative of kernels of real-world application codes: the classical elliptic test problem of a Poisson equation with homogeneous Dirichlet boundary conditions in two and three dimensions, a model of calcium induced calcium release in a heart cell, and a model of pancreatic beta cells in a computational islet.
Abstract: Modern architectures with multiple memory hierarchies in multi-core CPUs and coprocessors such as the massively parallel GPGPU and many-core Intel Xeon Phi offer opportunities to drastically speed up numerical kernels. Coprocessors, which supplement the work of the CPUs, generally have significantly more cores and threads than a multi-core CPU and use power more efficiently. The Intel Xeon Phi is a newer hardware released to the public only in 2013. Three modes of execution are available on the Intel Phi: (i) offloading, where the program is run on the CPU and segments of the code are moved to the Intel Phi, similar to GPGPU programming, (ii) native, where the program is run directly on the Intel Phi, and (iii) symmetric, where the program is run on the CPU and Phi jointly. We report the performance of three test problems whose structure is representative of kernels of real-world application codes: the classical elliptic test problem of a Poisson equation with homogeneous Dirichlet boundary conditions in two and three dimensions, a model of calcium induced calcium release in a heart cell, and a model of pancreatic beta cells in a computational islet.
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