Name
Abstract | ||
|---|---|---|
Scaling data-structures up to the increasing number of cores provided by modern systems is challenging. The quest for scalability is complicated by the non-uniform memory accesses (NUMA) of multi-socket machines that often prohibit the effective use of data-structures that span memory localities. Conventional shared memory data-structures using efficient non-blocking or lock-based implementations inevitably suffer from cache-coherency overheads, and non-local memory accesses between sockets. Multi-socket systems are common in cloud hardware, and many products are pushing shared memory systems to greater scales, thus making the ability to scale data-structures all the more pressing.
In this paper, we present the Distributed, Delegated Parallel Sections (DPS) runtime system that uses message-passing to move the computation on portions of data-structures between memory localities, while leveraging efficient shared memory implementations within each locality to harness efficient parallelism. We show through a series of data-structure scalability evaluations, and through an adaptation of memcached, that DPS enables strong data-structure scalability. DPS provides more than a factor of 3.1 improvements in throughput, and 23x decreases in tail latency for memcached.
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Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3361525.3361537 | Proceedings of the 20th International Middleware Conference |
Keywords | Field | DocType |
NUMA locality, concurrent data-structure, delegation | Data structure,Computer science,Delegation,Distributed computing,Scalability | Conference |
ISBN | Citations | PageRank |
978-1-4503-7009-7 | 0 | 0.34 |
References | Authors | |
0 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuxin Ren | 1 | 29 | 4.49 |
| Gabriel Parmer | 2 | 190 | 18.88 |