Name
Abstract | ||
|---|---|---|
As the expected emerging Non-Volatile Memory (NVM) technologies, such as 3DXPoint, are in production, there has been a recent push in the big data processing community from storage-centric towards memory-centric. Generally, in large-scale systems, distributed memory management through traditional network with TCP/IP protocol exposes performance bottleneck. Briefly, CPU- centric network involves context switching, memory copy etc. Remote Direct Memory Access (RDMA) technology reveals the tremendous performance advantage over than TCP/IP: Allowing access to remote memory directly bypassing OS kernel. In this paper, we propose Megalloc, a distributed NVM allocator exposes NVMs as a shared address space of a cluster of machines based-on RDMA. Firstly, it makes memory allocation metadata accessed directly by each machine, allocating NVM in coarse-grained way; secondly, adopting fine-grained memory chunk for applications to read or store data; finally, it guarantees high distributed memory allocation performance. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/NAS.2017.8026865 | 2017 International Conference on Networking, Architecture, and Storage (NAS) |
Keywords | Field | DocType |
Megalloc,distributed memory allocator,NVM-based cluster,nonvolatile memory technologies,big data processing community,large-scale systems,distributed memory management,TCP/IP protocol,CPU-centric network,remote direct memory access,RDMA technology,OS kernel,distributed NVM allocator,shared address space,memory allocation metadata,fine-grained memory chunk | Registered memory,Interleaved memory,Uniform memory access,Computer science,Distributed memory,Computer network,Real-time computing,Memory management,Memory map,Distributed shared memory,Flat memory model,Operating system | Conference |
ISBN | Citations | PageRank |
978-1-5386-3487-5 | 0 | 0.34 |
References | Authors | |
20 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Songping Yu | 1 | 8 | 4.89 |
| Nong Xiao | 2 | 649 | 116.15 |
| Ming-Zhu Deng | 3 | 8 | 3.20 |
| Yuxuan Xing | 4 | 3 | 5.10 |
| Fang Liu | 5 | 1188 | 125.46 |
| Wei Chen | 6 | 86 | 12.45 |