Paper Info
Title
Identifying Opportunities for Byte-Addressable Non-Volatile Memory in Extreme-Scale Scientific Applications
Abstract
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.
Year
DOI
Venue
2012
10.1109/IPDPS.2012.89
IPDPS
Keywords
Field
DocType
scientific application,memory workload characteristics,power efficiency improvement,memory access pattern,write-access latencies,identifying opportunities,hybrid nvram-dram memory system,global data,data structures,memory access patterns,extreme-scale scientific applications,system performance,mission-critical scientific applications,dram chips,non-volatile memory,hardware simulation,byte-addressable nonvolatile memory,memory power,exascale systems,low power,stack,extreme power challenge,byte-addressable non-volatile memory,possible power saving,heap,binary instrumentation tool,specific memory workload characteristic,long nvram write-access latency,hpc systems,nonvolatile memory,resource management,memory management
Registered memory,Interleaved memory,Semiconductor memory,Uniform memory access,Computer science,Non-volatile random-access memory,Parallel computing,Cache-only memory architecture,Memory management,Memory map
Conference
ISSN
ISBN
Citations 
1530-2075
978-1-4673-0975-2
36
PageRank 
References 
Authors
1.09
9
7
Name
Order
Citations
PageRank
Li, Dong176448.56
Vetter, Jeffrey22383186.44
Gabriel Marin369835.97
Collin McCurdy442727.04
Cristian Cira5391.49
Zhuo Liu611816.03
Weikuan Yu7104277.40