Identifying Opportunities for Byte-Addressable Non-Volatile Memory in Extreme-Scale Scientific Applications

Future exascale systems face extreme power challenges. To improve power efficiency of future HPC systems, non-volatile memory (NVRAM) technologies are being investigated as potential alternatives to existing memories technologies. NVRAMs use extremely low power when in standby mode, and have other p...

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Veröffentlicht in:2012 IEEE 26th International Parallel and Distributed Processing Symposium S. 945 - 956
Hauptverfasser: Dong Li, Vetter, J. S., Marin, G., McCurdy, C., Cira, C., Zhuo Liu, Weikuan Yu
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.05.2012
Schlagworte:
Instruments
Memory management
Nonvolatile memory
Phase change random access memory
Power demand
Resource management
ISBN:1467309753, 9781467309752
ISSN:1530-2075
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Zusammenfassung:Future exascale systems face extreme power challenges. To improve power efficiency of future HPC systems, non-volatile memory (NVRAM) technologies are being investigated as potential alternatives to existing memories technologies. NVRAMs use extremely low power when in standby mode, and have other performance and scaling benefits. Although previous work has explored the integration of NVRAM into various architecture and system levels, an open question remains: do specific memory workload characteristics of scientific applications map well onto NVRAMs' features when used in a hybrid NVRAM-DRAM memory system? Furthermore, are there common classes of data structures used by scientific applications that should be frequently placed into NVRAM?In this paper, we analyze several mission-critical scientific applications in order to answer these questions. Specifically, we develop a binary instrumentation tool to statistically report memory access patterns in stack, heap, and global data. We carry out hardware simulation to study the impact of NVRAM for both memory power and system performance. Our study identifies many opportunities for using NVRAM for scientific applications. In two of our applications, 31% and 27% of the memory working sets are suitable for NVRAM. Our simulations suggest at least 27% possible power savings and reveal that the performance of some applications is insensitive to relatively long NVRAM write-access latencies.
ISBN:1467309753
9781467309752
ISSN:1530-2075
DOI:10.1109/IPDPS.2012.89