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

机译:应用程序透明近记忆处理架构,具有内存通道网络

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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.
机译:服务器的物理内存容量预计会随着即将到来的非易失性存储器技术的部署大大增加。这是新兴数据密集型应用的欢迎改进。对于这种服务器具有成本效益,尽管如此,我们必须成本有效地提高计算吞吐量和内存带宽,随着存储容量的增加而不会损害应用程序准备。解决这一挑战,我们在本文中呈现了内存通道网络(MCN)架构。具体地,首先,我们提出了一种MCN DIMM,缓冲DIMM的延伸,其中一个名为MCN处理器的小但有能力的处理器与DIMM上的缓冲器设备集成,用于近存储器处理。其次,我们实施设备驱动程序在服务器中为主机和MCN处理器提供一个错觉,它们是通过以太网链路连接的独立异构节点。这些允许服务器中的主机和MCN处理器根据流行的分布式计算框架(如MPI和Spark)一起运行给定的数据密集型应用程序,没有主机硬件及其应用软件的任何变化,同时提供高的好处 - 主机和MCN处理器之间的带宽和低延迟通信通过内存通道。这样,MCN可以用作应用程序透明框架,其可以在服务器内无缝统一近存储器处理,并在这些服务器中分布计算以进行数据密集型应用。我们的仿真运行全软件堆栈显示,具有8个MCN DIMM的服务器提供4.56倍的吞吐量,并且比通过以太网链路连接的9个传统节点的集群消耗47.5%的时间,因为它有助于高达8.17倍的聚合DRAM带宽利用率。最后,我们展示了MCN与IBM Power8系统的可行性和实验缓冲DIMM。

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