Paper Info
Title
Design and Evaluation of Scalable Concurrent Queues for Many-Core Architectures
Abstract
As core counts increase and as heterogeneity becomes more common in parallel computing, we face the prospect of programming hundreds or even thousands of concurrent threads in a single shared-memory system. At these scales, even highly-efficient concurrent algorithms and data structures can become bottlenecks, unless they are designed from the ground up with throughput as their primary goal. In this paper, we present three contributions: (1) a characterization of queue designs in terms of modern multi- and many-core architectures, (2) the design of a high-throughput, linearizable, blocking, concurrent FIFO queue for many-core architectures that avoids the bottlenecks and pitfalls common in modern queue designs, and (3) a thorough evaluation of concurrent queue throughput across CPU, GPU, and co-processor devices. Our evaluation shows that focusing on throughput, rather than progress guarantees, allows our queue to scale to as much as three orders of magnitude (1000x) faster than lock-free and combining queues on GPU platforms and two times (2x) faster on CPU devices. These results deliver critical insights into the design of data structures for highly concurrent systems: (1) progress guarantees do not guarantee scalability, and (2) allowing an algorithm to block can increase throughput.
Year
DOI
Venue
2015
10.1145/2668930.2688048
ICPE
Keywords
Field
DocType
heterogeneous,gpu,queue,parallel programming,many-core,accelerator,high performance computing,algorithms
Data structure,Supercomputer,Computer science,Parallel computing,Queue,Thread (computing),Fifo queue,Throughput,Scalability,Distributed computing
Conference
Citations 
PageRank 
References 
8
0.56
13
Authors
2
Name
Order
Citations
PageRank
Thomas R. W. Scogland1877.56
Wu-chun Feng22812232.50