Subjects -> COMPUTER SCIENCE (Total: 2313 journals)
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COMPUTER SCIENCE (1305 journals)            First | 1 2 3 4 5 6 7 | Last

Showing 601 - 800 of 872 Journals sorted alphabetically
International Journal of Digital Enterprise Technology     Hybrid Journal   (Followers: 1)
International Journal of Digital Literacy and Digital Competence     Full-text available via subscription   (Followers: 6)
International Journal of Digital Signals and Smart Systems     Hybrid Journal   (Followers: 4)
International Journal of Education and Development using Information and Communication Technology     Open Access   (Followers: 9)
International Journal of Electrical and Computer Engineering     Open Access   (Followers: 8)
International Journal of Electronic Banking     Hybrid Journal   (Followers: 3)
International Journal of Electronic Business     Hybrid Journal   (Followers: 2)
International Journal of Electronic Commerce     Full-text available via subscription   (Followers: 10)
International Journal of Electronic Government Research     Full-text available via subscription   (Followers: 3)
International Journal of Embedded and Real-Time Communication Systems     Full-text available via subscription   (Followers: 9)
International Journal of Engineering and Manufacturing     Open Access   (Followers: 3)
International Journal of Engineering Science     Hybrid Journal   (Followers: 6)
International Journal of Entertainment Technology and Management     Hybrid Journal   (Followers: 1)
International Journal of Experimental Design and Process Optimisation     Hybrid Journal   (Followers: 5)
International Journal of Foundations of Computer Science     Hybrid Journal   (Followers: 3)
International Journal of Fuzzy Computation and Modelling     Hybrid Journal   (Followers: 2)
International Journal of Fuzzy System Applications     Full-text available via subscription   (Followers: 3)
International Journal of General Systems     Hybrid Journal   (Followers: 1)
International Journal of Granular Computing, Rough Sets and Intelligent Systems     Hybrid Journal   (Followers: 1)
International Journal of Green Computing     Full-text available via subscription  
International Journal of Grid and High Performance Computing     Full-text available via subscription   (Followers: 2)
International Journal of Grid and Utility Computing     Hybrid Journal  
International Journal of Handheld Computing Research     Full-text available via subscription  
International Journal of Heritage in the Digital Era     Full-text available via subscription   (Followers: 7)
International Journal of High Performance Computing and Networking     Hybrid Journal   (Followers: 4)
International Journal of High Performance Computing Applications     Hybrid Journal   (Followers: 4)
International Journal of High Performance Systems Architecture     Hybrid Journal   (Followers: 6)
International Journal of Human Capital and Information Technology Professionals     Full-text available via subscription   (Followers: 3)
International Journal of Human-Computer Interaction     Hybrid Journal   (Followers: 22)
International Journal of Human-Computer Studies     Hybrid Journal   (Followers: 20)
International Journal of Humanitarian Technology     Hybrid Journal   (Followers: 1)
International Journal of Humanities and Arts Computing     Hybrid Journal   (Followers: 11)
International Journal of Hybrid Intelligence     Hybrid Journal   (Followers: 1)
International Journal of ICT Research and Development in Africa     Full-text available via subscription   (Followers: 4)
International Journal of Imaging Systems and Technology     Hybrid Journal   (Followers: 1)
International Journal of Impact Engineering     Hybrid Journal   (Followers: 9)
International Journal of Industrial and Systems Engineering     Hybrid Journal   (Followers: 7)
International Journal of Industrial Electronics and Drives     Hybrid Journal   (Followers: 3)
International Journal of Information and Coding Theory     Hybrid Journal   (Followers: 6)
International Journal of Information and Communication Technology Education     Full-text available via subscription   (Followers: 13)
International Journal of Information Communication Technologies and Human Development     Full-text available via subscription   (Followers: 4)
International Journal of Information Quality     Hybrid Journal   (Followers: 3)
International Journal of Information Retrieval Research     Full-text available via subscription   (Followers: 28)
International Journal of Information Science and Management     Open Access   (Followers: 6)
International Journal of Information Science and Technology     Open Access   (Followers: 1)
International Journal of Information Systems and Management     Hybrid Journal   (Followers: 3)
International Journal of Information Systems and Project Management     Free   (Followers: 12)
International Journal of Information Systems and Software Engineering for Big Companies     Open Access   (Followers: 2)
International Journal of Information Technology and Computer Science     Open Access   (Followers: 3)
International Journal of Information Technology and Web Engineering     Hybrid Journal   (Followers: 2)
International Journal of Information Technology Project Management     Full-text available via subscription   (Followers: 9)
International Journal of Information Technology, Communications and Convergence     Hybrid Journal   (Followers: 14)
International Journal of Innovation in the Digital Economy     Full-text available via subscription   (Followers: 5)
International Journal of Innovative Computing and Applications     Hybrid Journal   (Followers: 3)
International Journal of Innovative Technology and Research     Open Access   (Followers: 1)
International Journal of Intelligence and Sustainable Computing     Hybrid Journal  
International Journal of Intelligence Science     Open Access   (Followers: 3)
International Journal of Intelligent Engineering Informatics     Hybrid Journal  
International Journal of Intelligent Enterprise     Hybrid Journal   (Followers: 1)
International Journal of Intelligent Information and Database Systems     Hybrid Journal   (Followers: 3)
International Journal of Intelligent Internet of Things Computing     Hybrid Journal   (Followers: 2)
International Journal of Intelligent Networks     Open Access  
International Journal of Intelligent Systems Technologies and Applications     Hybrid Journal   (Followers: 2)
International Journal of Intercultural Relations     Hybrid Journal   (Followers: 16)
International Journal of IT Standards and Standardization Research     Full-text available via subscription  
International Journal of IT/Business Alignment and Governance     Full-text available via subscription  
International Journal of Knowledge and Systems Science     Full-text available via subscription   (Followers: 1)
International Journal of Knowledge Engineering and Soft Data Paradigms     Hybrid Journal   (Followers: 1)
International Journal of Knowledge Society Research     Full-text available via subscription  
International Journal of Leadership in Education: Theory and Practice     Hybrid Journal   (Followers: 23)
International Journal of Logistics Research and Applications : A Leading Journal of Supply Chain Management     Hybrid Journal   (Followers: 16)
International Journal of Management & Information Technology     Open Access   (Followers: 2)
International Journal of Management Innovation Systems     Open Access  
International Journal of Mathematical Modelling & Computations     Open Access   (Followers: 3)
International Journal of Mathematical Sciences and Computing     Open Access  
International Journal of Mathematics & Computation     Full-text available via subscription  
International Journal of Mathematics in Operational Research     Hybrid Journal   (Followers: 2)
International Journal of Medical Engineering and Informatics     Hybrid Journal   (Followers: 4)
International Journal of Medical Informatics     Hybrid Journal   (Followers: 10)
International Journal of Metadata, Semantics and Ontologies     Hybrid Journal   (Followers: 9)
International Journal of Metaheuristics     Hybrid Journal   (Followers: 1)
International Journal of Mobile Communications     Hybrid Journal   (Followers: 8)
International Journal of Mobile Computing and Multimedia Communications     Full-text available via subscription   (Followers: 2)
International Journal of Mobile Network Design and Innovation     Hybrid Journal   (Followers: 1)
International Journal of Modeling, Simulation, and Scientific Computing     Hybrid Journal   (Followers: 3)
International Journal of Modelling, Identification and Control     Hybrid Journal   (Followers: 1)
International Journal of Modern Education and Computer Science     Open Access   (Followers: 2)
International Journal of Multimedia Data Engineering and Management     Full-text available via subscription   (Followers: 2)
International Journal of Multimedia Information Retrieval     Partially Free   (Followers: 8)
International Journal of Nanotechnology and Molecular Computation     Full-text available via subscription   (Followers: 4)
International Journal of Natural Computing Research     Hybrid Journal  
International Journal of Neural Systems     Hybrid Journal   (Followers: 4)
International Journal of Online Marketing     Full-text available via subscription   (Followers: 5)
International Journal of Organizational and Collective Intelligence     Hybrid Journal  
International Journal of Parallel, Emergent and Distributed Systems     Hybrid Journal   (Followers: 3)
International Journal of Pattern Recognition and Artificial Intelligence     Hybrid Journal   (Followers: 12)
International Journal of Performance Arts and Digital Media     Hybrid Journal   (Followers: 12)
International Journal of Pervasive Computing and Communications     Hybrid Journal   (Followers: 3)
International Journal of Polymer Science     Open Access   (Followers: 25)
International Journal of Process Systems Engineering     Hybrid Journal   (Followers: 1)
International Journal of Quantum Information     Hybrid Journal   (Followers: 6)
International Journal of Reasoning-based Intelligent Systems     Hybrid Journal  
International Journal of Reconfigurable and Embedded Systems     Open Access   (Followers: 6)
International Journal of Reconfigurable Computing     Open Access  
International Journal of Refractory Metals and Hard Materials     Hybrid Journal   (Followers: 5)
International Journal of Reliability, Quality and Safety Engineering     Hybrid Journal   (Followers: 14)
International Journal of Reliable and Quality E-Healthcare     Full-text available via subscription   (Followers: 2)
International Journal of Research Studies in Computing     Open Access  
International Journal of RF and Microwave Computer-Aided Engineering     Hybrid Journal   (Followers: 26)
International Journal of Sediment Research     Full-text available via subscription   (Followers: 2)
International Journal of Sensor Networks     Hybrid Journal   (Followers: 2)
International Journal of Service and Computing Oriented Manufacturing     Hybrid Journal   (Followers: 2)
International Journal of Shape Modeling     Hybrid Journal   (Followers: 1)
International Journal of Signs and Semiotic Systems     Full-text available via subscription  
International Journal of Smart Grid and Green Communications     Hybrid Journal   (Followers: 2)
International Journal of Social and Organizational Dynamics in IT     Full-text available via subscription  
International Journal of Sociotechnology and Knowledge Development     Full-text available via subscription   (Followers: 1)
International Journal of Soft Computing and Networking     Hybrid Journal   (Followers: 2)
International Journal of Soft Computing and Software Engineering     Open Access   (Followers: 13)
International Journal of Software Engineering and Knowledge Engineering     Hybrid Journal   (Followers: 6)
International Journal of Spatio-Temporal Data Science     Hybrid Journal  
International Journal of Speech Technology     Hybrid Journal   (Followers: 7)
International Journal of Strategic Change Management     Hybrid Journal   (Followers: 6)
International Journal of Strategic Communication     Hybrid Journal   (Followers: 5)
International Journal of Strategic Information Technology and Applications     Full-text available via subscription   (Followers: 1)
International Journal of Stress Management     Full-text available via subscription   (Followers: 6)
International Journal of Student Project Reporting     Hybrid Journal   (Followers: 8)
International Journal of Swarm Intelligence     Hybrid Journal   (Followers: 2)
International Journal of Swarm Intelligence Research     Full-text available via subscription   (Followers: 3)
International Journal of System Dynamics Applications     Full-text available via subscription  
International Journal of Systems Science     Hybrid Journal   (Followers: 2)
International Journal of Systems Science : Operations & Logistics     Hybrid Journal  
International Journal of Systems, Control and Communications     Hybrid Journal   (Followers: 6)
International Journal of Technoethics     Full-text available via subscription   (Followers: 2)
International Journal of Technology and Educational Marketing     Full-text available via subscription   (Followers: 2)
International Journal of Technology and Human Interaction     Full-text available via subscription   (Followers: 2)
International Journal of Technology Diffusion     Full-text available via subscription   (Followers: 1)
International Journal of Technology Marketing     Hybrid Journal   (Followers: 3)
International Journal of Telecommunications & Emerging Technologies     Full-text available via subscription   (Followers: 1)
International Journal of the Digital Human     Hybrid Journal   (Followers: 2)
International Journal of Trust Management in Computing and Communications     Hybrid Journal   (Followers: 1)
International Journal of Ultra Wideband Communications and Systems     Hybrid Journal  
International Journal of Virtual Reality     Open Access   (Followers: 1)
International Journal of Virtual Technology and Multimedia     Hybrid Journal   (Followers: 2)
International Journal of Web Services Research     Full-text available via subscription  
International Journal of Wireless and Microwave Technologies     Open Access   (Followers: 12)
International Journal of Wireless Information Networks     Hybrid Journal   (Followers: 2)
International Journal on Advances in ICT for Emerging Regions (ICTer)     Open Access   (Followers: 2)
International Journal on Artificial Intelligence Tools     Hybrid Journal   (Followers: 9)
International Journal on Digital Libraries     Hybrid Journal   (Followers: 550)
International Journal on Document Analysis and Recognition (IJDAR)     Hybrid Journal   (Followers: 2)
International Journal on Smart Sensing and Intelligent Systems     Open Access  
International Journal on Software Tools for Technology Transfer (STTT)     Hybrid Journal   (Followers: 4)
International Review of Law, Computers & Technology     Hybrid Journal   (Followers: 3)
International Review of Research in Open and Distance Learning     Open Access   (Followers: 24)
International Transaction of Electrical and Computer Engineers System     Open Access   (Followers: 2)
Internet of Things     Hybrid Journal   (Followers: 2)
Internet of Things and Cyber-Physical Systems     Open Access   (Followers: 1)
Internet Technology Letters     Hybrid Journal  
IoT     Open Access   (Followers: 1)
IPSJ Transactions on Computer Vision and Applications     Open Access   (Followers: 1)
Iran Journal of Computer Science     Hybrid Journal  
ISPRS Open Journal of Photogrammetry and Remote Sensing     Open Access   (Followers: 3)
ISSS Journal of Micro and Smart Systems     Hybrid Journal   (Followers: 3)
Issues in Informing Science and Information Technology     Open Access   (Followers: 2)
IT Journal Research and Development     Open Access  
ITM Web of Conferences     Open Access  
ITNOW     Hybrid Journal   (Followers: 1)
J-ENSITEC : Journal Of Engineering and Sustainable Technology     Open Access   (Followers: 4)
JISTEM : Journal of Information Systems and Technology Management     Open Access   (Followers: 6)
JMIR mHealth and uHealth     Open Access   (Followers: 3)
Johnson Matthey Technology Review     Open Access  
Jornal Brasileiro de TeleSSaúde     Open Access  
Journal of Computer Science & Systems Biology     Open Access   (Followers: 3)
Journal of 3D Printing in Medicine     Hybrid Journal  
Journal of Advanced Computer Science & Technology     Open Access   (Followers: 3)
Journal of Advances in Information Systems and Technology     Open Access  
Journal of Advances in Mathematics and Computer Science     Open Access  
Journal of Aggression Maltreatment & Trauma     Hybrid Journal   (Followers: 5)
Journal of Algorithms & Computational Technology     Open Access  
Journal of Altmetrics     Open Access   (Followers: 7)
Journal of Ambient Intelligence and Humanized Computing     Hybrid Journal   (Followers: 1)
Journal of Applied & Computational Mathematics     Open Access  
Journal of Applied and Computational Topology     Hybrid Journal  
Journal of Applied Bioinformatics & Computational Biology     Hybrid Journal   (Followers: 4)
Journal of Applied Communication Research     Hybrid Journal   (Followers: 10)
Journal of Applied Informatics and Technology     Open Access  
Journal of Applied Intelligent System     Open Access  
Journal of Applied Mathematics and Computation     Open Access   (Followers: 2)
Journal of Approximation Theory     Hybrid Journal   (Followers: 1)
Journal of Artificial Intelligence     Open Access   (Followers: 18)
Journal of Automated Reasoning     Hybrid Journal  
Journal of Automation and Control     Open Access   (Followers: 9)
Journal of Banking and Financial Technology     Hybrid Journal   (Followers: 1)
Journal of Big Data     Open Access   (Followers: 16)
Journal of Bioinformatics and Computational Biology     Hybrid Journal   (Followers: 19)
Journal of Biomedical Informatics     Partially Free   (Followers: 9)
Journal of Cases on Information Technology     Full-text available via subscription   (Followers: 3)
Journal of Chemical Information and Modeling     Hybrid Journal   (Followers: 18)
Journal of Chemical Theory and Computation     Hybrid Journal   (Followers: 21)

  First | 1 2 3 4 5 6 7 | Last

Similar Journals
Journal Cover
International Journal of High Performance Computing Applications
Journal Prestige (SJR): 0.348
Citation Impact (citeScore): 2
Number of Followers: 4  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1094-3420 - ISSN (Online) 1741-2846
Published by Sage Publications Homepage  [1174 journals]
  • Accelerating physics simulations with tensor processing units: An
           inundation modeling example

    • Free pre-print version: Loading...

      Authors: R Lily Hu, Damien Pierce, Yusef Shafi, Anudhyan Boral, Vladimir Anisimov, Sella Nevo, Yi-fan Chen
      Abstract: The International Journal of High Performance Computing Applications, Ahead of Print.
      Recent advancements in hardware accelerators such as Tensor Processing Units (TPUs) speed up computation time relative to Central Processing Units (CPUs) not only for machine learning but, as demonstrated here, also for scientific modeling and computer simulations. To study TPU hardware for distributed scientific computing, we solve partial differential equations (PDEs) for the physics simulation of fluids to model riverine floods. We demonstrate that TPUs achieve a two orders of magnitude speedup over CPUs. Running physics simulations on TPUs is publicly accessible via the Google Cloud Platform, and we release a Python interactive notebook version of the simulation.
      Citation: The International Journal of High Performance Computing Applications
      PubDate: 2022-06-03T10:31:34Z
      DOI: 10.1177/10943420221102873
       
  • Recovering single precision accuracy from Tensor Cores while surpassing
           the FP32 theoretical peak performance

    • Free pre-print version: Loading...

      Authors: Hiroyuki Ootomo, Rio Yokota
      Abstract: The International Journal of High Performance Computing Applications, Ahead of Print.
      Tensor Core is a mixed-precision matrix–matrix multiplication unit on NVIDIA GPUs with a theoretical peak performance of more than 300 TFlop/s on Ampere architectures. Tensor Cores were developed in response to the high demand of dense matrix multiplication from machine learning. However, many applications in scientific computing such as preconditioners for iterative solvers and low-precision Fourier transforms can exploit these Tensor Cores. To compute a matrix multiplication on Tensor Cores, we need to convert input matrices to half-precision, which results in loss of accuracy. To avoid this, we can keep the mantissa loss in the conversion using additional half-precision variables and use them for correcting the accuracy of matrix–matrix multiplication. Even with this correction, the use of Tensor Cores yields higher throughput compared to FP32 SIMT Cores. Nevertheless, the correcting capability of this method alone is limited, and the resulting accuracy cannot match that of a matrix multiplication on FP32 SIMT Cores. We address this problem and develop a high accuracy, high performance, and low power consumption matrix–matrix multiplication implementation using Tensor Cores, which exactly matches the accuracy of FP32 SIMT Cores while achieving superior throughput. The implementation is based on NVIDIA’s CUTLASS. We found that the key to achieving this accuracy is how to deal with the rounding inside Tensor Cores and underflow probability during the correction computation. Our implementation achieves 51 TFlop/s for a limited exponent range using FP16 Tensor Cores and 33 TFlop/s for full exponent range of FP32 using TF32 Tensor Cores on NVIDIA A100 GPUs, which outperforms the theoretical FP32 SIMT Core peak performance of 19.5 TFlop/s.
      Citation: The International Journal of High Performance Computing Applications
      PubDate: 2022-06-03T10:13:28Z
      DOI: 10.1177/10943420221090256
       
  • A fine-grained parallelization of the immersed boundary method

    • Free pre-print version: Loading...

      Authors: Andrew Kassen, Varun Shankar, Aaron L Fogelson
      Abstract: The International Journal of High Performance Computing Applications, Ahead of Print.
      We present new algorithms for the parallelization of Eulerian–Lagrangian interaction operations in the immersed boundary method. Our algorithms rely on two well-studied parallel primitives: key-value sort and segmented reduce. The use of these parallel primitives allows us to implement our algorithms on both graphics processing units (GPUs) and on other shared-memory architectures. We present strong and weak scaling tests on problems involving scattered points and elastic structures. Our tests show that our algorithms exhibit near-ideal scaling on both multicore CPUs and GPUs.
      Citation: The International Journal of High Performance Computing Applications
      PubDate: 2022-06-03T01:31:40Z
      DOI: 10.1177/10943420221083572
       
  • Corrigendum to ‘Unprecedented cloud resolution in a GPU-enabled
           full-physics atmospheric climate simulation on OLCF’s summit
           supercomputer’

    • Free pre-print version: Loading...

      Abstract: The International Journal of High Performance Computing Applications, Ahead of Print.

      Citation: The International Journal of High Performance Computing Applications
      PubDate: 2022-06-01T09:37:09Z
      DOI: 10.1177/10943420221103014
       
  • Matrix-free approaches for GPU acceleration of a high-order finite element
           hydrodynamics application using MFEM, Umpire, and RAJA

    • Free pre-print version: Loading...

      Authors: Arturo Vargas, Thomas M Stitt, Kenneth Weiss, Vladimir Z Tomov, Jean-Sylvain Camier, Tzanio Kolev, Robert N Rieben
      Abstract: The International Journal of High Performance Computing Applications, Ahead of Print.
      With the introduction of advanced heterogeneous computing architectures based on GPU accelerators, large-scale production codes have had to rethink their numerical algorithms and incorporate new programming models and memory management strategies in order to run efficiently on the latest supercomputers. In this work we discuss our co-design strategy to address these challenges and achieve performance and portability with MARBL, a next-generation multi-physics code in development at Lawrence Livermore National Laboratory. We present a two-fold approach, wherein new hardware is used to motivate both new algorithms and new abstraction layers, resulting in a single source application code suitable for a variety of platforms. Focusing on MARBL’s ALE hydrodynamics package, we demonstrate scalability on different platforms and highlight that many of our innovations have been contributed back to open-source software libraries, such as MFEM (finite element algorithms) and RAJA (kernel abstractions).
      Citation: The International Journal of High Performance Computing Applications
      PubDate: 2022-05-26T02:16:48Z
      DOI: 10.1177/10943420221100262
       
  • Performance analysis of relaxation Runge–Kutta methods

    • Free pre-print version: Loading...

      Authors: Marcin Rogowski, Lisandro Dalcin, Matteo Parsani, David E Keyes
      Abstract: The International Journal of High Performance Computing Applications, Ahead of Print.
      Recently, global and local relaxation Runge–Kutta methods have been developed for guaranteeing the conservation, dissipation, or other solution properties for general convex functionals whose dynamics are crucial for an ordinary differential equation solution. These novel time integration procedures have an application in a wide range of problems that require dynamics-consistent and stable numerical methods. The application of a relaxation scheme involves solving scalar nonlinear algebraic equations to find the relaxation parameter. Even though root-finding may seem to be a problem technically straightforward and computationally insignificant, we address the problem at scale as we solve full-scale industrial problems on a CPU-powered supercomputer and show its cost to be considerable. In particular, we apply the relaxation schemes in the context of the compressible Navier–Stokes equations and use them to enforce the correct entropy evolution. We use seven different algorithms to solve for the global and local relaxation parameters and analyze their strong scalability. As a result of this analysis, within the global relaxation scheme, we recommend using Brent’s method for problems with a low polynomial degree and of small sizes for the global relaxation scheme, while secant proves to be the best choice for higher polynomial degree solutions and large problem sizes. For the local relaxation scheme, we recommend secant. Further, we compare the schemes’ performance using their most efficient implementations, where we look at their effect on the timestep size, overhead, and weak scalability. We show the global relaxation scheme to be always more expensive than the local approach—typically 1.1–1.5 times the cost. At the same time, we highlight scenarios where the global relaxation scheme might underperform due to its increased communication requirements. Finally, we present an analysis that sets expectations on the computational overhead anticipated based on the system properties.
      Citation: The International Journal of High Performance Computing Applications
      PubDate: 2022-05-12T04:35:37Z
      DOI: 10.1177/10943420221085947
       
  • Very fast finite element Poisson solvers on lower precision accelerator
           hardware: A proof of concept study for Nvidia Tesla V100

    • Free pre-print version: Loading...

      Authors: Dustin Ruda, Stefan Turek, Dirk Ribbrock, Peter Zajac
      Abstract: The International Journal of High Performance Computing Applications, Ahead of Print.
      Recently, accelerator hardware in the form of graphics cards including Tensor Cores, specialized for AI, has significantly gained importance in the domain of high-performance computing. For example, NVIDIA’s Tesla V100 promises a computing power of up to 125 TFLOP/s achieved by Tensor Cores, but only if half precision floating point format is used. We describe the difficulties and discrepancy between theoretical and actual computing power if one seeks to use such hardware for numerical simulations, that is, solving partial differential equations with a matrix-based finite element method, with numerical examples. If certain requirements, namely low condition numbers and many dense matrix operations, are met, the indicated high performance can be reached without an excessive loss of accuracy. A new method to solve linear systems arising from Poisson’s equation in 2D that meets these requirements, based on “prehandling” by means of hier-archical finite elements and an additional Schur complement approach, is presented and analyzed. We provide numerical results illustrating the computational performance of this method and compare it to a commonly used (geometric) multigrid solver on standard hardware. It turns out that we can exploit nearly the full computational power of Tensor Cores and achieve a significant speed-up compared to the standard methodology without losing accuracy.
      Citation: The International Journal of High Performance Computing Applications
      PubDate: 2022-05-07T04:48:37Z
      DOI: 10.1177/10943420221084657
       
  • An analytical performance model of generalized hierarchical scheduling

    • Free pre-print version: Loading...

      Authors: Stephen Herbein, Tapasya Patki, Dong H Ahn, Sebastian Mobo, Clark Hathaway, Silvina Caíno-Lores, James Corbett, David Domyancic, Thomas RW Scogland, Bronis R de Supinski, Michela Taufer
      First page: 289
      Abstract: The International Journal of High Performance Computing Applications, Ahead of Print.
      High performance computing (HPC) workflows are undergoing tumultuous changes, including an explosion in size and complexity. Despite these changes, most batch job systems still use slow, centralized schedulers. Generalized hierarchical scheduling (GHS) solves many of the challenges that face modern workflows, but GHS has not been widely adopted in HPC. A major difficulty that hinders adoption is the lack of a performance model to aid in configuring GHS for optimal performance on a given application. We propose an analytical performance model of GHS, and we validate our proposed model with four different applications on a moderately-sized system. Our validation shows that our model is extremely accurate at predicting the performance of GHS, explaining 98.7% of the variance (i.e., an R2 statistic of 0.987). Our results also support the claim that GHS overcomes scheduling throughput problems; we measured throughput improvements of up to 270× on our moderately-sized system. We then apply our performance model to a pre-exascale system, where our model predicts throughput improvements of four orders of magnitude and provides insight into optimally configuring GHS on next generation systems.
      Citation: The International Journal of High Performance Computing Applications
      PubDate: 2022-03-26T07:28:43Z
      DOI: 10.1177/10943420211051039
       
  • Enhancing scalability of a matrix-free eigensolver for studying many-body
           localization

    • Free pre-print version: Loading...

      Authors: Roel Van Beeumen, Khaled Z. Ibrahim, Gregory D. Kahanamoku–Meyer, Norman Y. Yao, Chao Yang
      First page: 307
      Abstract: The International Journal of High Performance Computing Applications, Ahead of Print.
      We propose several techniques to enhance the parallel scalability of a matrix-free eigensolver designed for studying many-body localization (MBL) of quantum spin chain models with nearest-neighbor interactions and on-site disorder. This type of problem is computationally challenging because the dimension of the associated Hamiltonian matrix grows exponentially with respect to the number of spins L, and we need to average over different realizations of the random disorder to obtain relevant statistical behavior. For each disorder realization, we need to compute eigenvalues from different regions of the spectrum and their corresponding eigenvectors. In previous work, the interior eigenstates for a single eigenvalue problem are computed via the shift-and-invert Lanczos algorithm. Due to the extremely high memory footprint of the LU factorizations, this technique is not well suited for large L’s. For example, we need thousands of compute nodes on modern high performance computing infrastructures to go beyond L = 24. The matrix-free approach does not suffer from this memory bottleneck, however, its scalability is limited by a computation and communication load imbalance. To reduce this imbalance and to significantly enhance the scalability of the matrix-free eigensolver, we reorder the matrix and leverage the consistent space runtime, CSPACER. We also show its efficiency in managing irregular communication patterns at scale compared to optimized MPI non-blocking two-sided and one-sided RMA implementation variants. This effort enables us to study MBL for spin chains with a larger number of spins. The efficiency and effectiveness of the proposed algorithm is demonstrated by computing eigenstates on a massively parallel many-core high performance computer.
      Citation: The International Journal of High Performance Computing Applications
      PubDate: 2022-03-19T12:49:46Z
      DOI: 10.1177/10943420211060365
       
  • Productively accelerating positron emission tomography image
           reconstruction on graphics processing units with Julia

    • Free pre-print version: Loading...

      Authors: Michiel Van Gendt, Tim Besard, Stefaan Vandenberghe, Bjorn De Sutter
      First page: 320
      Abstract: The International Journal of High Performance Computing Applications, Ahead of Print.
      Research in medical imaging is hampered by a lack of programming languages that support productive, flexible programming as well as high performance. In search for higher quality imaging, researchers can ideally experiment with novel algorithms using rapid-prototyping languages such as Python. However, to speed up image reconstruction, computational resources such as those of graphics processing units (GPUs) need to be used efficiently. Doing so requires re-programming the algorithms in lower-level programming languages such as CUDA C/C++ or rephrasing them in terms of existing implementations of established algorithms in libraries. The former has a detrimental impact on research productivity and requires system-level programming expertise, and the latter puts severe constraints on the flexibility to research novel algorithms. Here, we investigate the use of the Julia scientific programming language in the domain of PET image reconstruction as a means to obtain both high performance (portability) on GPUs and high programmer productivity and flexibility, all at once, without requiring expert GPU programming knowledge. Using rapid-prototyping features of Julia, we developed basic and performance-optimized GPU implementations of baseline maximum likelihood expectation maximization (MLEM) positron emission tomography (PET) image reconstruction algorithms, as well as multiple existing algorithmic extensions. Thus, we mimic the effort that researchers would have to invest to evaluate the quality and performance potential of algorithms. We evaluate the obtained performance and compare it to state-of-the-art existing implementations. We also analyse and compare the required programming effort. With the Julia implementations, performance in line with existing GPU implementations written in the low-level, unproductive programming language CUDA C is achieved, while requiring much less programming effort, even less than what is needed for much less performant CPU implementations in C++. Switching to Julia as the programming language of choice can therefore boost the productivity of research into medical imaging and deliver excellent performance at a low cost in terms of programming effort.
      Citation: The International Journal of High Performance Computing Applications
      PubDate: 2022-03-22T09:13:52Z
      DOI: 10.1177/10943420211067520
       
  • Development of NCL equivalent serial and parallel python routines for
           meteorological data analysis

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      Authors: Jatin Gharat, Bipin Kumar, Leena Ragha, Amit Barve, Shaik Mohammad Jeelani, John Clyne
      First page: 337
      Abstract: The International Journal of High Performance Computing Applications, Ahead of Print.
      The NCAR Command Language (NCL) is a popular scripting language used in the geoscience community for weather data analysis and visualization. Hundreds of years of data are analyzed daily using NCL to make accurate weather predictions. However, due to its sequential nature of execution, it cannot properly utilize the parallel processing power provided by High-Performance Computing systems (HPCs). Until now very few techniques have been developed to make use of the multi-core functionality of modern HPC systems on these functions. In the recent trend, open-source languages are becoming highly popular because they support major functionalities required for data analysis and parallel computing. Hence, developers of NCL have decided to adopt Python as the future scripting language for analysis and visualization and to enable the geosciences community to play an active role in its development and support. This study focuses on developing some of the widely used NCL routines in Python. To deal with the analysis of large datasets, parallel versions of these routines are developed to work within a single node and make use of multi-core CPUs to achieve parallelism. Results show high accuracy between NCL and Python outputs and the parallel versions provided good scaling compared to their sequential counterparts.
      Citation: The International Journal of High Performance Computing Applications
      PubDate: 2022-03-22T06:41:30Z
      DOI: 10.1177/10943420221077110
       
  • Efficient high-precision integer multiplication on the GPU

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      Authors: Adrian P Dieguez, Margarita Amor, Ramón Doallo, Akira Nukada, Satoshi Matsuoka
      First page: 356
      Abstract: The International Journal of High Performance Computing Applications, Ahead of Print.
      The multiplication of large integers, which has many applications in computer science, is an operation that can be expressed as a polynomial multiplication followed by a carry normalization. This work develops two approaches for efficient polynomial multiplication: one approach is based on tiling the classical convolution algorithm, but taking advantage of new CUDA architectures, a novelty approach to compute the multiplication using integers without accuracy lossless; the other one is based on the Strassen algorithm, an algorithm that multiplies large polynomials using the FFT operation, but adapting the fastest FFT libraries for current GPUs and working on the complex field. Previous studies reported that the Strassen algorithm is an effective implementation for “large enough” integers on GPUs. Additionally, most previous studies do not examine the implementation of the carry normalization, but this work describes a parallel implementation for this operation. Our results show the efficiency of our approaches for short, medium, and large sizes.
      Citation: The International Journal of High Performance Computing Applications
      PubDate: 2022-03-21T01:30:24Z
      DOI: 10.1177/10943420221077964
       
  • AI4IO: A suite of AI-based tools for IO-aware scheduling

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      Authors: Michael R Wyatt, Stephen Herbein, Todd Gamblin, Michela Taufer
      First page: 370
      Abstract: The International Journal of High Performance Computing Applications, Ahead of Print.
      Traditional workload managers do not have the capacity to consider how IO contention can increase job runtime and even cause entire resource allocations to be wasted. Whether from bursts of IO demand or parallel file systems (PFS) performance degradation, IO contention must be identified and addressed to ensure maximum performance. In this paper, we present AI4IO (AI for IO), a suite of tools using AI methods to prevent and mitigate performance losses due to IO contention. AI4IO enables existing workload managers to become IO-aware. Currently, AI4IO consists of two tools: PRIONN and CanarIO. PRIONN predicts IO contention and empowers schedulers to prevent it. CanarIO mitigates the impact of IO contention when it does occur. We measure the effectiveness of AI4IO when integrated into Flux, a next-generation scheduler, for both small- and large-scale IO-intensive job workloads. Our results show that integrating AI4IO into Flux improves the workload makespan up to 6.4%, which can account for more than 18,000 node-h of saved resources per week on a production cluster in our large-scale workload.
      Citation: The International Journal of High Performance Computing Applications
      PubDate: 2022-04-04T03:39:21Z
      DOI: 10.1177/10943420221079765
       
  • Task-parallel in situ temporal compression of large-scale computational
           fluid dynamics data

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      Authors: Heather Pacella, Alec Dunton, Alireza Doostan, Gianluca Iaccarino
      First page: 388
      Abstract: The International Journal of High Performance Computing Applications, Ahead of Print.
      Present day computational fluid dynamics (CFD) simulations generate considerable amounts of data, sometimes on the order of TB/s. Often, a significant fraction of this data is discarded because current storage systems are unable to keep pace. To address this, data compression algorithms can be applied to data arrays containing flow quantities of interest (QoIs) to reduce the overall required storage. The matrix column interpolative decomposition (ID) can be implemented as a type of lossy compression for data matrices that factors the original data matrix into a product of two smaller factor matrices. One of these matrices consists of a subset of the columns of the original data matrix, while the other is a coefficient matrix which approximates the original data matrix columns as linear combinations of the selected columns. Motivating this work is the observation that the structure of ID algorithms makes them well suited for the asynchronous nature of task-based parallelism; they can operate independently on subdomains of the system of interest and, as a result, provide varied levels of compression. Using the task-based Legion programming model, a single-pass ID algorithm (SPID) for CFD applications is implemented. Performance studies, scalability, and the accuracy of the compression algorithm are presented for a benchmark analytical Taylor-Green vortex problem, as well as large-scale implementations of both low and high Reynolds number (Re) compressible Taylor-Green vortices using a high-order Navier-Stokes solver. In the case of the analytical solution, the resulting compressed solution was rank-one, with error on the order of machine precision. For the low-Re vortex, compression factors between 1000 and 10,000 were achieved for errors in the range 10−2–10−3. Similar error values were seen for the high-Re vortex, this time with compression factors between 100 and 1000. Moreover, strong and weak scaling results demonstrate that introducing SPID to solvers leads to negligible increases in runtime.
      Citation: The International Journal of High Performance Computing Applications
      PubDate: 2022-04-21T07:59:08Z
      DOI: 10.1177/10943420221085000
       
  • Performance portability in a real world application: PHAST applied to
           Caffe

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      Authors: Pablo Antonio Martínez, Biagio Peccerillo, Sandro Bartolini, José M García, Gregorio Bernabé
      First page: 419
      Abstract: The International Journal of High Performance Computing Applications, Ahead of Print.
      This work covers the PHAST Library’s employment, a hardware-agnostic programming library, to a real-world application like the Caffe framework. The original implementation of Caffe consists of two different versions of the source code: one to run on CPU platforms and another one to run on the GPU side. With PHAST, we aim to develop a single-source code implementation capable of running efficiently on CPU and GPU. In this paper, we start by carrying out a basic Caffe implementation performance analysis using PHAST. Then, we detail possible performance upgrades. We find that the overall performance is dominated by few ‘heavy’ layers. In refining the inefficient parts of this version, we find two different approaches: improvements to the Caffe source code and improvements to the PHAST Library itself, which ultimately translates into improved performance in the PHAST version of Caffe. We demonstrate that our PHAST implementation achieves performance portability on CPUs and GPUs. With a single source, the PHAST version of Caffe provides the same or even better performance than the original version of Caffe built from two different codebases. For the MNIST database, the PHAST implementation takes an equivalent amount of time as native code in CPU and GPU. Furthermore, PHAST achieves a speedup of 51% and a 49% with the CIFAR-10 database against native code in CPU and GPU, respectively. These results provide a new horizon for software development in the upcoming heterogeneous computing era.
      Citation: The International Journal of High Performance Computing Applications
      PubDate: 2022-03-21T12:53:22Z
      DOI: 10.1177/10943420221077107
       
  • Tree-based convolutional neural networks for object classification in
           segmented satellite images

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      Authors: Y Harold Robinson, S Vimal, Manju Khari, Fernando Carlos López Hernández, Rubén González Crespo
      Abstract: The International Journal of High Performance Computing Applications, Ahead of Print.
      Satellite images have a very high resolution, which make their automatic processing computationally costly, and they suffer from artifacts making their processing difficult. This paper describes a method for the effective semantic segmentation of satellite images, and compares different object classifiers in terms of accuracy and execution time. In the paper, the image spectrum is used to reduce the computational cost during the segmentation and classification steps. Firstly, artifacts are corrected from the satellite images for facilitating the feature extraction process. After this, semantic representation is used to gather the semantic regions of downscaled images. As the images are very large, this scaling down significantly reduces the computing time with little degradation in the coarse object detection results. A deep neural forest classifier finds potential regions before executing the pixel-based segmentation. Finally, in our experiments, boundary detection and several classifiers are evaluated to find the objects associated with these regions. The paper details the set-up for our tree-based convolutional neural network. The results indicate that this tree-based convolutional neural network outperforms the other surveyed techniques in the literature.
      Citation: The International Journal of High Performance Computing Applications
      PubDate: 2020-07-28T12:11:35Z
      DOI: 10.1177/1094342020945026
       
 
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