Characterizing emerging heterogeneous memory

Shen, Du; Liu, Xu; Lin, Felix Xiaozhu

doi:10.1145/2926697.2926702

Cited by 17 publications

(11 citation statements)

References 28 publications

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“…Du et. al [19] develop a PIN-based o ine pro ling tool to collect memory traces and provide guidance for placing data on HMS.…”

Section: Related Workmentioning

confidence: 99%

“…Our initial performance evaluation with HPC workloads (Section 2) shows that there is 1.09x-8.4x slowdown on NVM-based systems, depending on bandwidth and latency features of NVM. Because of the limitation of NVM, NVM is o en paired with a small fraction of DRAM to form a heterogeneous memory system (HMS) [8,10,13,19,24,26]. By selectively placing frequently accessed data in the small amount of DRAM available in HMS, we are able to exploit the cost and scaling bene ts of NVM while minimizing the limitation of NVM with DRAM.…”

Section: Introductionmentioning

confidence: 99%

“…In HMS, we assume that DRAM shares the same physical address space as NVM (but with di erent addresses) and DRAM memory allocation can be managed at the user level. is assumption has been widely used in the existing work [8,10,13,19,26].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Runtime Data Management on Non-Volatile Memory-based Heterogeneous Memory for Task-Parallel Programs

Ren

Liu

2018

SC18: International Conference for High Performance Computing, Networking, Storage and Analysis

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Non-volatile memory (NVM) provides a scalable and power-e cient solution to replace DRAM as main memory. However, because of relatively high latency and low bandwidth of NVM, NVM is often paired with DRAM to build a heterogeneous memory system (HMS). As a result, data objects of the application must be carefully placed to NVM and DRAM for best performance. In this paper, we introduce a lightweight runtime solution that automatically and transparently manage data placement on HMS without the requirement of hardware modi cations and disruptive change to applications. Leveraging online pro ling and performance models, the runtime characterizes memory access pa erns associated with data objects, and minimizes unnecessary data movement. Our runtime solution e ectively bridges the performance gap between NVM and DRAM. We demonstrate that using NVM to replace the majority of DRAM can be a feasible solution for future HPC systems with the assistance of a so ware-based data management.

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“…Du et. al [19] develop a PIN-based o ine pro ling tool to collect memory traces and provide guidance for placing data on HMS.…”

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Runtime Data Management on Non-Volatile Memory-based Heterogeneous Memory for Task-Parallel Programs

Ren

Liu

2018

SC18: International Conference for High Performance Computing, Networking, Storage and Analysis

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“…Current state-of-the-art approaches rely on detailed a priori application profiles to establish the relative priority of all of the application data structures [12,28,33]. However, such approaches have limited applicability for complex applications, applications exhibiting data-dependent variability in their execution, or requiring crossapplication-component data exchanges.…”

Section: Design Componentsmentioning

confidence: 99%

Unity

Jones

Brim

Vallée

et al. 2017

Proceedings of the 7th International Workshop on Runtime and Operating Systems for Supercomputers ROSS 2017

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This paper describes the vision for UNITY , a new high-performance computing focused data storage abstraction that places the entire memory hierarchy, including both traditionally separated memoryand file-based data storage, into one storage continuum. Through the use of a novel API and a set of services centered around a smart runtime system, UNITY is able to provide a number of valuable and interesting benefits. The unified storage space provides a scalable and resilient data environment that dynamically manages the mapping of data onto available resources based on multiple factors, including desired persistence and energy budget considerations. By eliminating the need for high-performance computing domain scientists to develop architecture-dependent optimizations for rapidly evolving data storage technologies, UNITY addresses both ease-of-use and performance.

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“…Our initial performance evaluation with HPC workloads (Section 2) shows that there is 1.09x-8.4x slowdown on NVM-based systems, depending on bandwidth and latency features of NVM. Because of the limitation of NVM, NVM is often paired with a small fraction of DRAM to form a heterogeneous memory system (HMS) [1][2][3][4][5][6][7] . By selectively placing frequently-accessed data in the small amount of DRAM available in HMS, we are able to exploit the cost and scaling benefits of NVM while minimizing the limitation of NVM with DRAM.…”

Section: Introductionmentioning

confidence: 99%

Unimem: Runtime Data Management on Non-Volatile Memory-Based Heterogeneous Main Memory for High Performance Computing

2021

J. Comput. Sci. Technol.

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Non-volatile memory (NVM) provides a scalable and power-efficient solution to replace dynamic random access memory (DRAM) as main memory. However, because of the relatively high latency and low bandwidth of NVM, NVM is often paired with DRAM to build a heterogeneous memory system (HMS). As a result, data objects of the application must be carefully placed to NVM and DRAM for the best performance. In this paper, we introduce a lightweight runtime solution that automatically and transparently manages data placement on HMS without the requirement of hardware modifications and disruptive change to applications. Leveraging online profiling and performance models, the runtime solution characterizes memory access patterns associated with data objects, and minimizes unnecessary data movement. Our runtime solution effectively bridges the performance gap between NVM and DRAM. We demonstrate that using NVM to replace the majority of DRAM can be a feasible solution for future HPC systems with the assistance of a software-based data management.

show abstract

Characterizing emerging heterogeneous memory

Cited by 17 publications

References 28 publications

Runtime Data Management on Non-Volatile Memory-based Heterogeneous Memory for Task-Parallel Programs

Runtime Data Management on Non-Volatile Memory-based Heterogeneous Memory for Task-Parallel Programs

Unity

Unimem: Runtime Data Management on Non-Volatile Memory-Based Heterogeneous Main Memory for High Performance Computing

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