Java for high performance computing

Taboada, Guillermo L.; Touriño, Juan; Doallo, Ramón

doi:10.1145/1596655.1596661

Cited by 24 publications

References 37 publications

(49 reference statements)

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Cross‐platform management of intelligent objects behaviors in serious virtual environments

Rodriguez

Puig

Esteva

2011

Computer Animation & Virtual

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In this paper, we present a generic interaction framework that controls intelligent objects' actions in different virtual world (VW) platforms. These actions are based on the state of external platform‐independent artificial intelligence‐based systems such as multi‐agent and rule‐based systems. We have evaluated the proposed framework by means of two intelligent objects, a door and a noticeboard, incorporating them in Second Life and OpenWonderland VWs. These objects allow to work along three advanced aspects of a serious virtual environment: it is a dynamic space where participants are synchronously informed about activities evolution inside the virtual space, it can integrate processes and information coming from the real world, and it needs norms to organize participants actions, to define actions consequences, and to prevent undesired participants behaviors. Copyright © 2011 John Wiley & Sons, Ltd.

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Cross‐platform management of intelligent objects behaviors in serious virtual environments

Rodriguez

Puig

Esteva

2011

Computer Animation & Virtual

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Device level communication libraries for high‐performance computing in Java

Taboada

Touriño

Doallo

et al. 2011

Concurrency and Computation

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SUMMARYSince its release, the Java programming language has attracted considerable attention from the highperformance computing (HPC) community because of its portability, high programming productivity, and built-in multithreading and networking support. As a consequence, several initiatives have been taken to develop a high-performance Java message-passing library to program distributed memory architectures, such as clusters. The performance of Java message-passing applications relies heavily on the communications performance. Thus, the design and implementation of low-level communication devices that support messagepassing libraries is an important research issue in Java for HPC. MPJ Express is our Java message-passing implementation for developing high-performance parallel Java applications. Its public release currently contains three communication devices: the first one is built using the Java New Input/Output (NIO) package for the TCP/IP; the second one is specifically designed for the Myrinet Express library on Myrinet; and the third one supports thread-based shared memory communications. Although these devices have been successfully deployed in many production environments, previous performance evaluations of MPJ Express suggest that the buffering layer, tightly coupled with these devices, incurs a certain degree of copying overhead, which represents one of the main performance penalties. This paper presents a more efficient Java message-passing communications device, based on Java Input/Output sockets, that avoids this buffering overhead. Moreover, this device implements several strategies, both in the communication protocol and in the HPC hardware support, which optimizes Java message-passing communications. In order to evaluate its benefits, this paper analyzes the performance of this device comparatively with other Java and native message-passing libraries on various high-speed networks, such as Gigabit Ethernet, Scalable Coherent Interface, Myrinet, and InfiniBand, as well as on a shared memory multicore scenario. The reported communication overhead reduction encourages the upcoming incorporation of this device in MPJ Express (http://mpj-express.org). Copyright

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Evaluating ARM HPC clusters for scientific workloads

Maqbool

Fox

2015

Concurrency and Computation

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The power consumption of modern high-performance computing (HPC) systems that are built using power hungry commodity servers is one of the major hurdles for achieving Exascale computation. Several efforts have been made by the HPC community to encourage the use of low-powered system-on-chip (SoC) embedded processors in large-scale HPC systems. These initiatives have successfully demonstrated the use of ARM SoCs in HPC systems, but there is still a need to analyze the viability of these systems for HPC platforms before a case can be made for Exascale computation. The major shortcomings of current ARM-HPC evaluations include a lack of detailed insights about performance levels on distributed multicore systems and performance levels for benchmarking in large-scale applications running on HPC. In this paper, we present a comprehensive evaluation of results that covers major aspects of server and HPC benchmarking for ARMbased SoCs. For the experiments, we built an unconventional cluster of ARM Cortex-A9s that is referred to as Weiser and ran single-node benchmarks (STREAM, Sysbench, and PARSEC) and multi-node scientific benchmarks (High-performance Linpack (HPL), NASA Advanced Supercomputing (NAS) Parallel Benchmark, and Gadget-2) in order to provide a baseline for performance limitations of the system. Based on the experimental results, we claim that the performance of ARM SoCs depends heavily on the memory bandwidth, network latency, application class, workload type, and support for compiler optimizations. During server-based benchmarking, we observed that when performing memory intensive benchmarks for database transactions, x86 performed 12% better for multithreaded query processing. However, ARM performed four times better for performance to power ratios for a single core and 2.6 times better on four cores. We noticed that emulated double precision floating point in Java resulted in three to four times slower performance as compared with the performance in C for CPU-bound benchmarks. Even though Intel x86 performed slightly better in computation-oriented applications, ARM showed better scalability in I/O bound applications for shared memory benchmarks. We incorporated the support for ARM in the MPJ-Express runtime and performed comparative analysis of two widely used message passing libraries. We obtained similar results for network bandwidth, large-scale application scaling, floating-point performance, and energy-efficiency for clusters in message passing evaluations (NBP and Gadget 2 with MPJ-Express and MPICH). Our findings can be used to evaluate the energy efficiency of ARM-based clusters for server workloads and scientific workloads and to provide a guideline for building energy-efficient HPC clusters.

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Java for high performance computing

Cited by 24 publications

References 37 publications

Cross‐platform management of intelligent objects behaviors in serious virtual environments

Cross‐platform management of intelligent objects behaviors in serious virtual environments

Device level communication libraries for high‐performance computing in Java

Evaluating ARM HPC clusters for scientific workloads

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