Shen, Mueller Collaborate on Improving Memory Performance
Dr. Xipeng Shen, associate professor, and Dr. Frank Mueller, professor of computer science at NC State, have been awarded $470,000 by the National Science Foundation (NSF) to support their research proposal entitled “Improving Memory Performance on Fused Architectures Through Compiler and Runtime Innovations.”
The award will run from August 1, 2015 to July 31, 2018.
Abstract – Contemporary architectures are adopting an integrated design of conventional CPUs with accelerators on the same die with access to the same memory, albeit with different coherence models. Examples include AMD's Fusion architecture, Intel's integrated main-stream CPU/GPU product line, and NVIDIA Tegra's integrated graphics processor family.
Integrated GPUs feature shared caches and a common memory interconnect with multicore CPUs, which intensify resource contention in the memory hierarchy. This creates new challenges for data locality, task partitioning and scheduling, as well as program transformations. Most significantly, a program running on GPU warps and CPU cores may adversely affect performance and power of one another.
The objective of this work is to understand these novel implications of fused architectures by studying their effects, qualifying their causes and quantifying the impacts on performance and energy efficiency. We propose to advance the state-of-the-art by creating spheres of isolation between CPU and GPU execution via novel systems mechanisms and compiler transformations that reduce cross-boundary contention with respect to shared hardware resources. This synergy between systems and compiler techniques has the potential to significantly improve performance and power guarantees for co-scheduling pgrams fragments on fused architectures.
Impact: The proposed work, if successful, has the potential to transform resource allocation and scheduling at the systems level and compiler optimizations at the program level to create a synergistic development environment with significant performance and power improvements and vastly increased isolation suitable for synergistic co-deployment of programs crossing boundaries on innovative fused architectures.
For more information on Dr. Shen, click here.
For more information on Dr. Mueller, click here.
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