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Application-Transparent Near-Memory Processing Architecture with Memory Channel Network

Application-Transparent Near-Memory Processing Architecture with Memory Channel Network
Alian, MohammadMin, Seung WonAsgharimoghaddam, HadiDhar, AshutoshWang, Dong KaiRoewer, ThomasMcPadden, AdamOHalloran, OliverChen, DemingXiong, JinjunKim, Dae HoonHwu, Wen-meiKim, Nam Sung
DGIST Authors
Kim, Dae Hoon
Issue Date
51st Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 2018, 802-814
The physical memory capacity of servers is expected to increase drastically with deployment of the forthcoming non-volatile memory technologies. This is a welcomed improvement for emerging data-intensive applications. For such servers to be cost-effective, nonetheless, we must cost-effectively increase compute throughput and memory bandwidth commensurate with the increase in memory capacity without compromising application readiness. Tackling this challenge, we present Memory Channel Network (MCN) architecture in this paper. Specifically, first, we propose an MCN DIMM, an extension of a buffered DIMM where a small but capable processor called MCN processor is integrated with a buffer device on the DIMM for near-memory processing. Second, we implement device drivers to give the host and MCN processors in a server an illusion that they are independent heterogeneous nodes connected through an Ethernet link. These allow the host and MCN processors in a server to run a given data-intensive application together based on popular distributed computing frameworks such as MPI and Spark without any change in the host processor hardware and its application software, while offering the benefits of high-bandwidth and low-latency communications between the host and the MCN processors over memory channels. As such, MCN can serve as an application-Transparent framework which can seamlessly unify near-memory processing within a server and distributed computing across such servers for data-intensive applications. Our simulation running the full software stack shows that a server with 8 MCN DIMMs offers 4.56X higher throughput and consume 47.5% less energy than a cluster with 9 conventional nodes connected through Ethernet links, as it facilitates up to 8.17X higher aggregate DRAM bandwidth utilization. Lastly, we demonstrate the feasibility of MCN with an IBM POWER8 system and an experimental buffered DIMM. © 2018 IEEE.
Related Researcher
  • Author Kim, Dae Hoon Computer Architecture and Systems Lab
  • Research Interests Computer Architecture and Systems; Virtualization; Cloud Computing
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Department of Information and Communication EngineeringComputer Architecture and Systems Lab2. Conference Papers

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