Title: Transparent Offloading and Mapping (TOM):Enabling Programmer-Transparent Near-Data Processing in GPU Systems
Topic: Data offloading for multiple 3D memory-stacked GPGPU architechture to alleviate the memory bandwidth bottleneck.
Idea: alleviate the memory bandwitdh bottleneck mainly by 2 phases: 1) use compiler-based technique to determine potentially offload candidate by calculate the benifit from offload, and make the offload decision at runtime, 2) use a data mapping technique that doesn’t need programmers’ effort by combining both hardware/software then determine the mapping method based on a small period observation using memory access patterns.
Contribution: 1)propose a new data offloading mechanism that statically identifies instruction blocks benefit from offloading, and dynamically decides whether candidate can be offload in runtime 2) propose a new programmer-transparent data mapping mechanism exploits the predictability in memory access patterns of to co-locate offloaded code and data in the same memory stack 3)comprehensively evaluate the mechanism using 10 memory-intensive GPGPU applications across different system configurations
The result shows that their mechanism is practical and effective approach to enabling programmer-transparent near-data processing in GPU systems.