Thread-Safe SHMEM Extensions

George

Concurrency and Computation

et al. 2015

SUMMARYDiminishing returns from increased clock frequencies and instruction-level parallelism have forced computer architects to adopt architectures that exploit wider parallelism through multiple processor cores. While emerging many-core architectures have progressed at a remarkable rate, concerns arise regarding the performance and productivity of numerous parallel-programming tools for application development. Development of parallel applications on many-core processors often requires developers to familiarize themselves with unique characteristics of a target platform while attempting to maximize performance and maintain correctness of their applications. The family of partitioned global address space (PGAS) programming models comprises the current state of the art in balancing performance and programmability. One such PGAS approach is SHMEM, a lightweight, shared-memory programming library that has demonstrated high performance and productivity potential for parallel-computing systems with distributed-memory architectures. In the paper, we present research, design, and analysis of a new SHMEM infrastructure specifically crafted for low-level PGAS on modern and emerging many-core processors featuring dozens of cores and more. Our approach (with a new library known as TSHMEM) is investigated and evaluated atop two generations of Tilera architectures, which are among the most sophisticated and scalable many-core processors to date, and is intended to enable similar libraries atop other architectures now emerging. In developing TSHMEM, we explore design decisions and their impact on parallel performance for the Tilera TILE-Gx and TILEPro many-core architectures, and then evaluate the designs and algorithms within TSHMEM through microbenchmarking and applications studies with other communication libraries. Our results with barrier primitives provided by the Tilera libraries show dissimilar performance between the TILE-Gx and TILEPro; therefore, TSHMEM's barrier design takes an alternative approach and leverages the on-chip mesh network to provide consistent low-latency performance. In addition, our experiments with TSHMEM show that naive collective algorithms consistently outperformed linear distributed collective algorithms when executed in an SMP-centric environment. In leveraging these insights for the design of TSHMEM, our approach outperforms the OpenSHMEM reference implementation, achieves similar to positive performance over OpenMP and OSHMPI atop MPICH, and supports similar libraries in delivering high-performance parallel computing to emerging many-core systems.

Section: Discussionmentioning

confidence: 99%

Low‐level PGAS computing on many‐core processors with TSHMEM

George

Concurrency and Computation

et al. 2015

Proceedings of the 8th International Conference on Partitioned Global Address Space Programming Models

“…A SHMEM thread safety extension was proposed by ten Bruggencate et al [19]. This proposal captures existing thread safety extensions that are provided by the Cray SHMEM library.…”

Section: Related Workmentioning

confidence: 98%

Contexts

Dinan¹,

Flajšlik²

2014

This paper introduces a proposed extension to the OpenSHMEM parallel programming model, called communication contexts. Contexts introduce a new construct that allows a programmer to generate independent streams of communication operations. In hybrid executions where multiple threads execute within an Open-SHMEM process, contexts eliminate interference between threads, and enable the OpenSHMEM library to map operations generated by threads to private communication resource sets. By providing thread isolation, contexts eliminate synchronization overheads and enable each thread to drive a similar set of resources and achieve performance comparable to an OpenSHMEM process. In conventional, single-threaded execution, contexts provide greater control over ordering of operations and can improve communication and computation overlap. A detailed description of the contexts interface and its implementation for the Portals 4 network programming interface is described. The implementation is evaluated using Mandelbrot set and integer sorting (IS) benchmarks. Contexts provide a 25% performance improvement for Mandelbrot by eliminating thread interference and enabling pipelining, and a 35% improvement was achieved for IS by enabling more effective communication/computation overlap.

Proceedings of the 8th International Conference on Partitioned Global Address Space Programming Models

“…This also means that problems within the context of one team/space are relatively isolated from the rest of the application, minimising their impact as well. Other significant implications could be in multi-threading environments where teams could be groups of threads [22]. This could allow for a more natural way of providing the extra context that such threading models require, but is out of the scope of this paper and so is left for future work.…”

Section: Introductionmentioning

confidence: 96%

Extending the OpenSHMEM Memory Model to Support User-Defined Spaces

Welch

Pophale²,

Shamis

et al. 2014

OpenSHMEM is an open standard for SHMEM libraries.With the standardisation process complete, the community is looking towards extending the API for increasing programmer flexibility and extreme scalability. According to the current OpenSHMEM specification (revision 1.1), allocation of symmetric memory is collective across all PEs executing the application. For better work sharing and memory utilisation, we are proposing the concepts of teams and spaces for OpenSHMEM that together allow allocation of memory only across user-specified teams. Through our implementation we show that by using teams we can confine memory allocation and usage to only the PEs that actually communicate via symmetric memory. We provide our preliminary results that demonstrate creating spaces for teams allows for less consumption of memory resources than the current alternative. We also examine the impact of our extensions on Scalable Synthetic Compact Applications #3 (SSCA3), which is a sensor processing and knowledge formation kernel involving file I/O, and show that up to 30% of symmetric memory allocation can be eliminated without affecting the correctness of the benchmark.