Abstract
While GPUs are designed to hide memory latency with massive multi-threading, the tremendous demands for memory bandwidth and power consumption constrain the system performance scaling. In this paper, we propose a hybrid graphics memory architecture with different memory technologies (DRAM, STT-RAM, and RRAM), to improve the memory bandwidth and reduce the power consumption. In addition, we present an adaptive data migration mechanism that exploits various memory access patterns of GPGPU applications for further memory power reduction. We evaluate our design with a set of multi-threaded GPU workloads. Compared to traditional GDDR5 memory, our design leads to 16% of GPU system power reduction, and improves the system throughput and energy efficiency by 12% and 33%.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
