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Scientific applications produce vast amounts of data, posing grand challenges in the underlying data management and analytic tasks. Progressive compression is a promising way to address this problem, as it allows for on-demand data…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-05-02 Yanliang Li , Wenbo Li , Qian Gong , Qing Liu , Norbert Podhorszki , Scott Klasky , Xin Liang , Jieyang Chen

While application profiling has been a mainstay in the HPC community for years, profiling of MPI and other communication middleware has not received the same degree of exploration. This paper adds to the discussion of MPI profiling,…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-02-20 Riley Shipley , Garrett Hooten , David Boehme , Derek Schafer , Anthony Skjellum , Olga Pearce

Increasing heterogeneity in HPC architectures and compiler advancements have led to OpenMP being frequently used to enable computations on heterogeneous devices. However, the efficient movement of data on heterogeneous computing platforms…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-09-10 Luke Marzen , Akash Dutta , Ali Jannesari

Modified policy iteration (MPI) is a dynamic programming algorithm that combines elements of policy iteration and value iteration. The convergence of MPI has been well studied in the context of discounted and average-cost MDPs. In this…

Machine Learning · Computer Science 2024-02-16 Yashaswini Murthy , Mehrdad Moharrami , R. Srikant

Leading HPC systems achieve their status through use of highly parallel devices such as NVIDIA GPUs or Intel Xeon Phi many-core CPUs. The concept of performance portability across such architectures, as well as traditional CPUs, is vital…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-11-10 Alan Gray , Kevin Stratford

Many modern and emerging applications must process increasingly large volumes of data. Unfortunately, prevalent computing paradigms are not designed to efficiently handle such large-scale data: the energy and performance costs to move this…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-07-31 Saugata Ghose , Amirali Boroumand , Jeremie S. Kim , Juan Gómez-Luna , Onur Mutlu

Particle-in-Cell (PIC) Monte Carlo (MC) simulations are central to plasma physics but face increasing challenges on heterogeneous HPC systems due to excessive data movement, synchronization overheads, and inefficient utilization of multiple…

DASH is a library of distributed data structures and algorithms designed for running the applications on modern HPC architectures, composed of hierarchical network interconnections and stratified memory. DASH implements a PGAS (partitioned…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-03-07 Kamran Idrees , Tobias Fuchs , Colin W. Glass

Hardware heterogeneity is here to stay for high-performance computing. Large-scale systems are currently equipped with multiple GPU accelerators per compute node and are expected to incorporate more specialized hardware in the future. This…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-10-05 Polykarpos Thomadakis , Nikos Chrisochoides

The efficiency and scalability of MPI collective operations, in particular the broadcast operation, plays an integral part in high performance computing applications. MPICH, as one of the contemporary widely-used MPI software stacks,…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-03-23 Huan Zhou , Vladimir Marjanovic , Christoph Niethammer , José Gracia

Asynchronous Many-Task (AMT) systems offer a potential solution for efficiently programming complicated scientific applications on extreme-scale heterogeneous architectures. However, they exhibit different communication needs from…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-03-18 Jiakun Yan , Hartmut Kaiser , Marc Snir

Finely tuning MPI applications and understanding the influence of keyparameters (number of processes, granularity, collective operationalgorithms, virtual topology, and process placement) is critical toobtain good performance on…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-01-10 Tom Cornebize , Arnaud Legrand

The modular composite representation (MCR) is a computing model that represents information with high-dimensional integer vectors using modular arithmetic. Originally proposed as a generalization of the binary spatter code model, it aims to…

Machine Learning · Computer Science 2025-11-14 Marco Angioli , Christopher J. Kymn , Antonello Rosato , Amy Loutfi , Mauro Olivieri , Denis Kleyko

High resolution simulations of polar ice-sheets play a crucial role in the ongoing effort to develop more accurate and reliable Earth-system models for probabilistic sea-level projections. These simulations often require a massive amount of…

Computational Engineering, Finance, and Science · Computer Science 2022-04-12 Jerry Watkins , Max Carlson , Kyle Shan , Irina Tezaur , Mauro Perego , Luca Bertagna , Carolyn Kao , Matthew J. Hoffman , Stephen F. Price

Remote Memory Access (RMA) is an emerging mechanism for programming high-performance computers and datacenters. However, little work exists on resilience schemes for RMA-based applications and systems. In this paper we analyze fault…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-10-20 Maciej Besta , Torsten Hoefler

Exascale systems will suffer failures hourly. HPC programmers rely mostly on application-level checkpoint and a global rollback to recover. In recent years, techniques reducing the number of rolling back processes have been implemented via…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-06-06 Kiril Dichev , Kirk Cameron , Dimitrios Nikolopoulos

Modern Artificial Intelligence (AI) applications are increasingly utilizing multi-tenant deep neural networks (DNNs), which lead to a significant rise in computing complexity and the need for computing parallelism. ReRAM-based…

Emerging Technologies · Computer Science 2024-08-12 Bojing Li , Duo Zhong , Xiang Chen , Chenchen Liu

Many modern, high-performance systems increase the cumulated node-bandwidth by offering more than a single communication network and/or by having multiple connections to the network. Efficient algorithms and implementations for collective…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-01-16 Jesper Larsson Träff

FASTEST-3D is an MPI-parallel finite-volume flow solver based on block-structured meshes that has been developed at the University of Erlangen-Nuremberg since the early 1990s. It can be used to solve the laminar or turbulent incompressible…

Performance · Computer Science 2013-03-20 Christoph Scheit , Georg Hager , Jan Treibig , Stefan Becker , Gerhard Wellein

Modern computing systems suffer from the dichotomy between computation on one side, which is performed only in the processor (and accelerators), and data storage/movement on the other, which all other parts of the system are dedicated to.…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-05-14 Onur Mutlu , Saugata Ghose , Juan Gómez-Luna , Rachata Ausavarungnirun