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Parallelism in Seismic Computing
Surveys in Geophysics, 1989This paper describes a vectorized and parallelized implementation of a two-dimensional pseudo-spectral seismic elastic model and of a (frequency-domain) seismic migration algorithm on the (tightly-coupled) vector multiprocessor IBM 3090 VF. Performance data of alternative parallel implementations on an LCAP (loosely coupled system of array processors ...
P. Sguazzero, Manuel Kindelan, A. Kamel
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Parallel computational geometry [PDF]
Algorithmica, 1985 We present efficient parallel algorithms for several basic problems in computational geometry: convex hulls, Voronoi diagrams, detecting line segment intersections, triangulating simple polygons, minimizing a circumscribing triangle, and recursive data-structures for three-dimensional queries.
Leonidas J. Guibas +4 more
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parallel: A command for parallel computing
The Stata Journal: Promoting communications on statistics and Stata, 2019The parallel package allows parallel processing of tasks that are not interdependent. This allows all flavors of Stata to take advantage of multiprocessor machines. Even Stata/MP users can benefit because many community-contributed programs are not automatically parallelized but could be under our framework.
Brian Quistorff, George G. Vega Yon
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IEEE International Solid-State Circuits Conference, 2020
Non-volatile memory (NVM) based computing-in-memory (CIM) shows significant advantages in handling deep learning tasks for artificial intelligence (AI) applications.
Qi Liu +14 more
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Non-volatile memory (NVM) based computing-in-memory (CIM) shows significant advantages in handling deep learning tasks for artificial intelligence (AI) applications.
Qi Liu +14 more
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2015
Scientific computing has become an indispensable tool in numerous fields, such as physics, mechanics, biology,finance and industry. For example, it enables us, thanks to efficient algorithms adapted to current computers, tosimulate, without the help of models or experimentations, the deflection of beams in bending, the sound level in a theater room or ...
Magoules, F., Roux, F.-X., Houzeaux, G.
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Scientific computing has become an indispensable tool in numerous fields, such as physics, mechanics, biology,finance and industry. For example, it enables us, thanks to efficient algorithms adapted to current computers, tosimulate, without the help of models or experimentations, the deflection of beams in bending, the sound level in a theater room or ...
Magoules, F., Roux, F.-X., Houzeaux, G.
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Parallel Computer Architecture
2009The possibility for a parallel execution of computations strongly depends on the architecture of the execution platform. This chapter gives an overview of the general structure of parallel computers which determines how computations of a program can be mapped to the available resources, such that a parallel execution is obtained.
Gudula Rünger, Thomas Rauber
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Proceedings of the 11th annual international symposium on Computer architecture - ISCA '84, 1984
The Pringle is a 64 processor MIMD computer with a 64 M (8 bit) instructions per second execution rate. (Copies are running at Purdue and Washington.) The Pringle runs programs written for the Configurable, Highly Parallel (CHiP) Computer. That is, the Pringle executes the 64 separate instruction streams as well as the interconnection (phase) stream ...
Lawrence H. Snyder +3 more
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The Pringle is a 64 processor MIMD computer with a 64 M (8 bit) instructions per second execution rate. (Copies are running at Purdue and Washington.) The Pringle runs programs written for the Configurable, Highly Parallel (CHiP) Computer. That is, the Pringle executes the 64 separate instruction streams as well as the interconnection (phase) stream ...
Lawrence H. Snyder +3 more
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On programming parallel computers
ACM SIGPLAN Notices, 1975In this paper, I will make some general observations about how computers should be programmed, and how programs should be compiled. I will restrict my attention to programming computers to solve numerical analysis problems, although most of my remarks can be applied to other problem areas as well.
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Computing dominators in parallel
Information Processing Letters, 1987Abstract We present a fast parallel algorithm for computing the dominators of a directed acyclic graph. The model of computation used in a parallel random access machine that allows simultaneous reads but prohibits simultaneous writes into the same memory location.
Shaunak Pawagi +2 more
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