Name
Title | ||
|---|---|---|
NVMalloc: Exposing an Aggregate SSD Store as a Memory Partition in Extreme-Scale Machines |
Abstract | ||
|---|---|---|
DRAM is a precious resource in extreme-scale machines and is increasingly becoming scarce, mainly due to the growing number of cores per node. On future multi-peta flop and exa flop machines, the memory pressure is likely to be so severe that we need to rethink our memory usage models. Fortunately, the advent of non-volatile memory (NVM) offers a unique opportunity in this space. Current NVM offerings possess several desirable properties, such as low cost and power efficiency, but suffer from high latency and lifetime issues. We need rich techniques to be able to use them alongside DRAM. In this paper, we propose a novel approach for exploiting NVM as a secondary memory partition so that applications can explicitly allocate and manipulate memory regions therein. More specifically, we propose an NVMalloc library with a suite of services that enables applications to access a distributed NVM storage system. We have devised ways within NVMalloc so that the storage system, built from compute node-local NVM devices, can be accessed in a byte-addressable fashion using the memory mapped I/O interface. Our approach has the potential to re-energize out-of-core computations on large-scale machines by having applications allocate certain variables through NVMalloc, thereby increasing the overall memory capacity available. Our evaluation on a 128-core cluster shows that NVMalloc enables applications to compute problem sizes larger than the physical memory in a cost-effective manner. It can bring more performance/efficiency gain with increased computation time between NVM memory accesses or increased data access locality. In addition, our results suggest that while NVMalloc enables transparent access to NVM-resident variables, the explicit control it provides is crucial to optimize application performance. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/IPDPS.2012.90 | IPDPS |
Keywords | Field | DocType |
extreme-scale machines,current nvm offering,physical memory,aggregate ssd store,secondary memory partition,memory usage model,memory pressure,nvm storage system,overall memory capacity,nvm memory access,non-volatile memory,memory region,memory partition,resource management,power efficiency,nonvolatile memory,cost effectiveness,data access,parallel processing,non volatile memory,storage system,dram,fuses | Registered memory,Interleaved memory,Semiconductor memory,Uniform memory access,Physical address,Computer science,Parallel computing,NVM Express,Memory management,Distributed computing,Auxiliary memory | Conference |
ISSN | Citations | PageRank |
1530-2075 | 36 | 1.17 |
References | Authors | |
14 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chao Wang | 1 | 404 | 27.12 |
| Sudharshan S. Vazhkudai | 2 | 396 | 24.98 |
| Xiaosong Ma | 3 | 1117 | 68.36 |
| Fei Meng | 4 | 113 | 14.50 |
| Youngjae Kim | 5 | 590 | 61.25 |
| Christian Engelmann | 6 | 953 | 60.46 |