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X-WR-CALDESC:Events for Northeastern University College of Engineering
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SUMMARY:Malith Jayaweera PhD Dissertation Defense
DESCRIPTION:Name:\nMalith Jayaweera \nTitle:\nEnergy-Aware Transformations for Affine Programs on GPUs \nDate:\n8/6/2024 \nTime:\n10:00:00 AM\nCommittee Members:\nProf. David Kaeli (Co-advisor)\nProf. Yanzhi Wang (Co-advisor)\nDr. Norman Rubin\nProf. Martin Kong (Ohio State University) \nAbstract:\nGraphics Processing Units (GPUs) have been increasingly used to accelerate workloads ranging from high performance computing to machine learning. Development of high-level programming languages\, improved compilers\, and runtime drivers have helped to accelerate the widespread adoption of GPUs. Given the wider adoption and ever-increasing computing capabilities\, the power consumption of GPUs is quickly becoming a critical factor. Furthermore\, the GPU micro-architecture differs from vendor to vendor\, and even between hardware generations of the same vendor. Also\, program variants with similar performance could differ in energy consumption due to the difference in utilization of GPU resources such as Streaming Multiprocessors (SMs) or memory. Despite performance improvements in compilation techniques\, energy-aware code generation for heterogeneous GPUs has not been aggressively explored. \nIn this dissertation\, we first identify the potential for energy-aware compilation techniques for GPUs. Next\, we use these insights to study loop tiling\, which is a popular loop transformation that has been successfully applied to computational domains such as linear algebra\, deep neural networks and iterative stencils. We then propose an energy-aware tile size selection for affine programs to generate energy-efficient code targeting GPUs. \nWe also investigate the challenging problem of optimizing the scheduling of complex sparse tensor algebra and expressions on GPUs\, with a focus on maximizing parallelism utilization to unlock optimal performance. We perform a comprehensive examination of the search space for sparse tensor expression scheduling\, seeking to characterize the intricate inter-relationships between kernel characteristics\, GPU architecture\, and hardware constraints such as memory bandwidth limitations\, to inform optimal scheduling decisions.
URL:https://coe.northeastern.edu/event/malith-jayaweera-phd-dissertation-defense/
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CREATED:20240517T125640Z
LAST-MODIFIED:20240603T184608Z
UID:44084-1722960000-1722963600@coe.northeastern.edu
SUMMARY:LeetCode Mock Interviews – CommLab Drop-In Workshops
DESCRIPTION:Join the CommLab any Tuesday from 4-5 PM for our weekly LeetCode Mock Interview Workshop via Zoom. This workshop is tailored towards programming jobs and prior coding knowledge is expected. Boost your LeetCode problem-solving confidence for interviews by building your speaking skills while solving programming problems.
URL:https://coe.northeastern.edu/event/leetcode-mock-interviews-commlab-drop-in-workshops/2024-08-06/
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