Log-based abnormal task detection and root cause analysis for spark
Application delays caused by abnormal tasks arecommon problems in big data computing
frameworks. Anabnormal task in Spark, which may run slowly withouterror or warning logs …
frameworks. Anabnormal task in Spark, which may run slowly withouterror or warning logs …
Integrated access to big data polystores through a knowledge-driven framework
J McHugh, PE Cuddihy, JW Williams… - … Conference on Big …, 2017 - ieeexplore.ieee.org
The recent successes of commercial cognitive and AI applications have cast a spotlight on
knowledge graphs and the benefits of consuming structured semantic data. Today …
knowledge graphs and the benefits of consuming structured semantic data. Today …
LADRA: Log-based abnormal task detection and root-cause analysis in big data processing with Spark
As big data processing is being widely adopted by many domains, massive amount of
generated data become more reliant on the parallel computing platforms for analysis …
generated data become more reliant on the parallel computing platforms for analysis …
A scalable parallel lsqr algorithm for solving large-scale linear system for tomographic problems: a case study in seismic tomography
Least Squares with QR-factorization (LSQR) method is a widely used Krylov subspace
algorithm to solve sparse rectangu-lar linear systems for tomographic problems. Traditional …
algorithm to solve sparse rectangu-lar linear systems for tomographic problems. Traditional …
[图书][B] Full-3D seismic waveform inversion: theory, software and practice
This book introduces a methodology for solving the seismic inverse problem using purely
numerical solutions of 3D wave equations and free of the approximations or simplifications …
numerical solutions of 3D wave equations and free of the approximations or simplifications …
An optimized parallel LSQR algorithm for seismic tomography
The LSQR algorithm developed by Paige and Saunders (1982) is considered one of the
most efficient and stable methods for solving large, sparse, and ill-posed linear (or …
most efficient and stable methods for solving large, sparse, and ill-posed linear (or …
The Gaia AVU–GSR parallel solver: Preliminary studies of a LSQR-based application in perspective of exascale systems
Abstract The Gaia Astrometric Verification Unit–Global Sphere Reconstruction (AVU–GSR)
Parallel Solver aims to find the astrometric parameters for∼ 1 0 8 stars in the Milky Way, the …
Parallel Solver aims to find the astrometric parameters for∼ 1 0 8 stars in the Milky Way, the …
Simulation of 3D centimeter-scale continuum tumor growth at sub-millimeter resolution via distributed computing
DA Goodin, HB Frieboes - Computers in biology and medicine, 2021 - Elsevier
Simulation of cm-scale tumor growth has generally been constrained by the computational
cost to numerically solve the associated equations, with models limited to representing mm …
cost to numerically solve the associated equations, with models limited to representing mm …
Tuning performance of Spark programs
H Zhang, Z Liu, L Wang - 2018 IEEE International Conference …, 2018 - ieeexplore.ieee.org
Along with the explosive growth of data, there is a great demand to speedup the ability to
process them. Although there are several platforms such as Spark that have made analysis …
process them. Although there are several platforms such as Spark that have made analysis …
The Gaia AVU–GSR solver: CPU+ GPU parallel solutions for linear systems solving and covariances calculation toward exascale systems
V Cesare, U Becciani, A Vecchiato… - … for Astronomy VIII, 2024 - spiedigitallibrary.org
We GPU ported with CUDA the solver module of the Astrometric Verification Unit–Global
Sphere Reconstruction (AVU–GSR) pipeline for the ESA Gaia mission. The code finds the …
Sphere Reconstruction (AVU–GSR) pipeline for the ESA Gaia mission. The code finds the …