GLB: Lifeline-based Global Load Balancing library in X10

We present GLB, a programming model and an associated implementation that can handle a wide range of irregular paral- lel programming problems running over large-scale distributed systems. GLB is applicable both to problems that are easily load-balanced via static scheduling and to problems that are hard to statically load balance. GLB hides the intricate syn- chronizations (e.g., inter-node communication, initialization and startup, load balancing, termination and result collection) from the users. GLB internally uses a version of the lifeline graph based work-stealing algorithm proposed by Saraswat et al. Users of GLB are simply required to write several pieces of sequential code that comply with the GLB interface. GLB then schedules and orchestrates the parallel execution of the code correctly and efficiently at scale. We have applied GLB to two representative benchmarks: Betweenness Centrality (BC) and Unbalanced Tree Search (UTS). Among them, BC can be statically load-balanced whereas UTS cannot. In either case, GLB scales well-- achieving nearly linear speedup on different computer architectures (Power, Blue Gene/Q, and K) -- up to 16K cores

Task Packing: Efficient task scheduling in unbalanced parallel programs to maximize CPU utilization

Load imbalance in parallel systems can be generated by external factors to the currently running applications like operating system noise or the underlying hardware like a heterogeneous cluster. HPC applications working on irregular data structures can also have difficulties to balance their computations across the parallel tasks. In this article we extend, improve and evaluate more deeply the Task Packing mechanism proposed in a previous work. The main idea of the mechanism is to concentrate the idle cycles of unbalanced applications in such a way that one or more CPUs are freed from execution. To achieve this, CPUs are stressed with just useful work of the parallel application tasks, provided performance is not degraded. The packing is solved by an algorithm based on the Knapsack problem, in a minimum number of CPUs and using oversubscription. We design and implement a more efficient version of such mechanism. To that end, we perform the Task Packing “in place”, taking advantage of idle cycles generated at synchronization points of unbalanced applications. Evaluations are carried out on a heterogeneous platform using FT and miniFE benchmarks. Results showed that our proposal generates low overhead. In addition the amount of freed CPUs are related to a load imbalance metric which can be used as a prediction for it.Peer ReviewedPostprint (author's final draft

On the conditions for efficient interoperability with threads: An experience with PGAS languages using Cray communication domains

Today's high performance systems are typically built from shared memory nodes connected by a high speed network. That architecture, combined with the trend towards less memory per core, encourages programmers to use a mixture of message passing and multithreaded programming. Unfortunately, the advantages of using threads for in-node programming are hindered by their inability to efficiently communicate between nodes. In this work, we identify some of the performance problems that arise in such hybrid programming environments and characterize conditions needed to achieve high communication performance for multiple threads: addressability of targets, separability of communication paths, and full direct reachability to targets. Using the GASNet communication layer on the Cray XC30 as our experimental platform, we show how to satisfy these conditions. We also discuss how satisfying these conditions is influenced by the communication abstraction, implementation constraints, and the interconnect messaging capabilities. To evaluate these ideas, we compare the communication performance of a thread-based node runtime to a process-based runtime. Without our GASNet extensions, thread communication is significantly slower than processes - up to 21x slower. Once the implementation is modified to address each of our conditions, the two runtimes have comparable communication performance. This allows programmers to more easily mix models like OpenMP, CILK, or pthreads with a GASNet-based model like UPC, with the associated performance, convenience and interoperability advantages that come from using threads within a node. © 2014 ACM

A comparison using APPL and PVM for a parallel implementation of an unstructured grid generation program

Efforts to parallelize the VGRIDSG unstructured surface grid generation program are described. The inherent parallel nature of the grid generation algorithm used in VGRIDSG was exploited on a cluster of Silicon Graphics IRIS 4D workstations using the message passing libraries Application Portable Parallel Library (APPL) and Parallel Virtual Machine (PVM). Comparisons of speed up are presented for generating the surface grid of a unit cube and a Mach 3.0 High Speed Civil Transport. It was concluded that for this application, both APPL and PVM give approximately the same performance, however, APPL is easier to use

Unbalanced tree search on a manycore system using the GPI programming model

The recent developments in computer architectures progress towards systems with large core count (Manycore) which expose more parallelism to applications. Some applications named irregular and unbalanced applications demand a dynamic and asynchronous load balance implementation to utilize the full performance a Manycore system. For example, the recently established Graph500 benchmark aims at such applications. The UTS benchmark characterizes the performance of such irregular and unbalanced computations with a tree-structured search space that requires continuous dynamic load balancing. GPI is a PGAS API that delivers the full performance of RDMA-enabled networks directly to the application. Its programming model focuses the use of one-sided asynchronous communication, overlapping computation and communication. In this paper we address the dynamic load balancing requirements of unbalanced applications using the GPI programming model. Using the UTS benchmark, we detail the implementation of a work stealing algorithm using GPI and present the performance results. Our performance evaluation shows significant improvements when compared with the optimized MPI version with a maximum performance of 9.5 billion nodes per second on 3072 cores

Overlay-Centric Load Balancing: Applications to UTS and B&B

International audienceTo deal with dynamic load balancing in large scale distributed systems, we propose to organize computing resources following a logical peer-to-peer overlay and to distribute the load according to the so-defined overlay. We use a tree as a logical structure connecting distributed nodes and we balance the load according to the size of induced subtrees. We conduct extensive experiments involving up to 1000 computing cores and provide a throughout analysis of different properties of our generic approach for two different applications, namely, the standard Unbalanced Tree Search and the more challenging parallel Branch-and-Bound algorithm. Substantial improvements are reported in comparison with the classical random work stealing and two finely tuned application specific strategies taken from the literature

A Highly Optimized Skeleton for Unbalanced and Deep Divide-And-Conquer Algorithms on Multi-Core Clusters

Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG [Abstract] Efficiently implementing the divide-and-conquer pattern of parallelism in distributed memory systems is very relevant, given its ubiquity, and difficult, given its recursive nature and the need to exchange tasks and data among the processors. This task is noticeably further complicated in the presence of multi-core systems, where hybrid parallelism must be exploited to attain the best performance, and when unbalanced and deep workloads are considered, as additional measures must be taken to load balance and avoid deep recursion problems. In this manuscript a parallel skeleton that fulfills all these requirements while providing high levels of usability is presented. In fact, the evaluation shows that our proposal is on average 415.32% faster than MPI codes and 229.18% faster than MPI + OpenMP benchmarks, while offering an average improvement in the programmability metrics of 131.04% over MPI alternatives and 155.18% over MPI + OpenMP solutions.This research was supported by the Ministry of Science and Innovation of Spain (PID2019-104184RB-I00 and PID2019-104834GB-I00, AEI/FEDER/EU, 10.13039/501100011033) and the predoctoral Grant of Millán Álvarez Ref. BES-2017-081320), and by the Xunta de Galicia co-founded by the European Regional Development Fund (ERDF) under the Consolidation Programme of Competitive Reference Groups (ED431C 2018/19 and ED431C 2021/30). We acknowledge also the support from the Centro Singular de Investigación de Galicia “CITIC” and the Centro Singular de Investigación en Tecnoloxías Intelixentes “CiTIUS”, funded by Xunta de Galicia and the European Union (European Regional Development Fund- Galicia 2014-2020 Program), by Grants ED431G 2019/01 and ED431G 2019/04. We also acknowledge the Centro de Supercomputación de Galicia (CESGA). Open Access funding provided thanks to the CRUE-CSIC agreement with Springer NatureXunta de Galicia; ED431C 2018/19Xunta de Galicia; ED431C 2021/30Xunta de Galicia; ED431G 2019/01Xunta de Galicia; ED431G 2019/0