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Previous work has shown that there are two major complexity barriers in the synthesis of fault-tolerant distributed programs: (1) generation of fault-span, the set of states reachable in the presence of faults, and (2) resolving deadlock…

Distributed, Parallel, and Cluster Computing · Computer Science 2009-12-15 Fuad Abujarad , Borzoo Bonakdarpour , Sandeep S. Kulkarni

Comprehending the performance bottlenecks at the core of the intricate hardware-software interactions exhibited by highly parallel programs on HPC clusters is crucial. This paper sheds light on the issue of automatically asynchronous MPI…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-09-06 Ayesha Afzal , Georg Hager , Stefano Markidis , Gerhard Wellein

In this paper we analyze, evaluate, and improve the performance of training generalized linear models on modern CPUs. We start with a state-of-the-art asynchronous parallel training algorithm, identify system-level performance bottlenecks,…

Machine Learning · Computer Science 2018-12-20 Nikolas Ioannou , Celestine Dünner , Kornilios Kourtis , Thomas Parnell

We present a language extension for parallel quantum programming to (1) remove ambiguities concerning parallelism in current quantum programming languages and (2) facilitate space-time tradeoff investigations in quantum computing. While the…

The purpose of this book is to help you program shared-memory parallel systems without risking your sanity. Nevertheless, you should think of the information in this book as a foundation on which to build, rather than as a completed…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-06-13 Paul E. McKenney

OpenCL, along with CUDA, is one of the main tools used to program GPGPUs. However, it allows running the same code on multi-core CPUs too, making it a rival for the long-established OpenMP. In this paper we compare OpenCL and OpenMP when…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-03-24 Kamran Karimi

In multi-core systems, various factors like inter-process communication, dependency, resource sharing and scheduling, level of parallelism, synchronization, number of available cores etc. influence the extent of possible High Performance…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-02-15 Urmila Shrawankar , Mayuri Joshi

The current trend of multicore architectures on shared memory systems underscores the need of parallelism. While there are some programming model to express parallelism, thread programming model has become a standard to support these system…

Distributed, Parallel, and Cluster Computing · Computer Science 2010-12-13 D. T. Hasta , A. B. Mutiara

Graphics processing units (GPU) had evolved from a specialized hardware capable to render high quality graphics in games to a commodity hardware for effective processing blocks of data in a parallel schema. This evolution is particularly…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-03-26 Luis Cabellos

Parallel batched data structures are designed to process synchronized batches of operations in a parallel computing model. In this paper, we propose parallel combining, a technique that implements a concurrent data structure from a parallel…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-11-14 Vitaly Aksenov , Petr Kuznetsov , Anatoly Shalyto

Recent advances in computing architectures and networking are bringing parallel computing systems to the masses so increasing the number of potential users of these kinds of systems. In particular, two important technological evolutions are…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-04-05 Gabriele D'Angelo , Moreno Marzolla

Real-time systems applications usually consist of a set of concurrent activities with timing-related properties. Developing these applications requires programming paradigms that can effectively handle the specification of concurrent…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-03-21 Luis Miguel Pinho

This paper presents implementation details and empirical results for a hybrid message passing and shared memory paralleliziation of the adaptive integral method (AIM). AIM is implemented on a (near) petaflop supercomputing cluster of…

Computational Engineering, Finance, and Science · Computer Science 2010-10-08 Fangzhou Wei , Ali E. Yılmaz

To harness the full benefit of new computing platforms, it is necessary to develop software with parallel computing capabilities. This is no less true for statisticians than for astrophysicists. The R programming language, which is perhaps…

Computation · Statistics 2017-09-08 George Ostrouchov , Wei-Chen Chen , Drew Schmidt

This paper consists of three parts. The first part provides a unified programming model for heterogeneous computing with CPU and accelerator (like GPU, FPGA, Google TPU, Atos QPU, and more) technologies. To some extent, this new programming…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-05-31 Yuqing Xiong

Exascale systems, expected to emerge by the end of the next decade, will require the exploitation of billion-way parallelism at multiple hierarchical levels in order to achieve the desired sustained performance. The task of assessing future…

Distributed, Parallel, and Cluster Computing · Computer Science 2011-09-27 Matthew Anderson , Maciej Brodowicz , Hartmut Kaiser , Thomas Sterling

Polymorphism in programming languages enables code reuse. Here, we show that polymorphism has broad applicability far beyond computations for technical computing: parallelism in distributed computing, presentation of visualizations of…

Programming Languages · Computer Science 2014-11-07 Jiahao Chen , Alan Edelman

We present a simple and easy to apply methodology for using high-level self-submitting parallel job queues in an MPI environment. Using C++, we implemented a library of functions, MPQueue, both for testing our concepts and for use in real…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-04-23 John M. Neuberger , Nandor Sieben , James W. Swift

The complexity of heterogeneous computing architectures, as well as the demand for productive and portable parallel application development, have driven the evolution of parallel programming models to become more comprehensive and complex…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-10-31 Anjia Wang , Xinyao Yi , Yonghong Yan

In typical embedded applications, the precise execution time of the program does not matter, and it is sufficient to meet a real-time deadline. However, modern applications in information security have become much more time-sensitive, due…

Cryptography and Security · Computer Science 2020-05-07 Pantea Kiaei , Patrick Schaumont