Storm
| Autor: | Haggai Eran, Michael Cui, Boris Pismenny, Yiying Zhang, Michael Wei, Marcos K. Aguilera, Liran Liss, Aasheesh Kolli, Dan Tsafrir, Stanko Novakovic, Yizhou Shan |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
010302 applied physics
Hardware_MEMORYSTRUCTURES Software_OPERATINGSYSTEMS Remote direct memory access Datagram Computer science InfiniBand 020206 networking & telecommunications 02 engineering and technology STREAMS Data structure computer.software_genre 01 natural sciences 0103 physical sciences Scalability 0202 electrical engineering electronic engineering information engineering Operating system Cache State (computer science) Host (network) computer |
| Zdroj: | SYSTOR |
| Popis: | RDMA technology enables a host to access the memory of a remote host without involving the remote CPU, improving the performance of distributed in-memory storage systems. Previous studies argued that RDMA suffers from scalability issues, because the NIC's limited resources are unable to simultaneously cache the state of all the concurrent network streams. These concerns led to various software-based proposals to reduce the size of this state by trading off performance. We revisit these proposals and show that they no longer apply when using newer RDMA NICs in rack-scale environments. In particular, we find that one-sided remote memory primitives lead to better performance as compared to the previously proposed unreliable datagram and kernel-based stacks. Based on this observation, we design and implement Storm, a transactional dataplane utilizing one-sided read and write-based RPC primitives. We show that Storm outperforms eRPC, FaRM, and LITE by 3.3x, 3.6x, and 17.1x, respectively, on an InfiniBand cluster with Mellanox ConnectX-4 NICs. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|