Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Cambier, Leopold"'
Publikováno v:
AIAA Scitech 2021 Forum
Development of highly scalable and robust algorithms for large-scale CFD simulations has been identified as one of the key ingredients to achieve NASA's CFD Vision 2030 goals. In order to improve simulation capability and to effectively leverage new
Externí odkaz:
http://arxiv.org/abs/2101.01763
We present TaskTorrent, a lightweight distributed task-based runtime in C++. TaskTorrent uses a parametrized task graph to express the task DAG, and one-sided active messages to trigger remote tasks asynchronously. As a result the task DAG is complet
Externí odkaz:
http://arxiv.org/abs/2009.10697
Autor:
Cambier, Léopold, Sarkar, Rahul
We study the problem $x_{b,\omega} := \text{arg min}_{x \in \mathcal{S}} \|(A + \omega I)^{-1/2} (b - Ax)\|_2$, with $A = A^*$, for a subspace $\mathcal{S}$ of $\mathbb{F}^n$ ($\mathbb{F} = \mathbb{R}$ or $\mathbb{C}$), and $\omega > -\lambda_{min}(A
Externí odkaz:
http://arxiv.org/abs/2008.11154
We describe a second-order accurate approach to sparsifying the off-diagonal blocks in the hierarchical approximate factorizations of sparse symmetric positive definite matrices. The norm of the error made by the new approach depends quadratically, n
Externí odkaz:
http://arxiv.org/abs/2007.00789
Autor:
Cambier, Léopold, Bhiwandiwalla, Anahita, Gong, Ting, Nekuii, Mehran, Elibol, Oguz H, Tang, Hanlin
Training with larger number of parameters while keeping fast iterations is an increasingly adopted strategy and trend for developing better performing Deep Neural Network (DNN) models. This necessitates increased memory footprint and computational re
Externí odkaz:
http://arxiv.org/abs/2001.05674
Autor:
Cambier, Léopold, Chen, Chao, Boman, Erik G, Rajamanickam, Sivasankaran, Tuminaro, Raymond S., Darve, Eric
We propose a new algorithm for the fast solution of large, sparse, symmetric positive-definite linear systems, spaND -- sparsified Nested Dissection. It is based on nested dissection, sparsification and low-rank compression. After eliminating all int
Externí odkaz:
http://arxiv.org/abs/1901.02971
Autor:
Chen, Chao, Cambier, Leopold, Boman, Erik G., Rajamanickam, Sivasankaran, Tuminaro, Raymond S., Darve, Eric
A hierarchical solver is proposed for solving sparse ill-conditioned linear systems in parallel. The solver is based on a modification of the LoRaSp method, but employs a deferred-compression technique, which provably reduces the approximation error
Externí odkaz:
http://arxiv.org/abs/1811.11248
Autor:
Xu, Zixi, Cambier, Léopold, Rouet, François-Henry, L'Eplatennier, Pierre, Huang, Yun, Ashcraft, Cleve, Darve, Eric
The efficient compression of kernel matrices, for instance the off-diagonal blocks of discretized integral equations, is a crucial step in many algorithms. In this paper, we study the application of Skeletonized Interpolation to construct such factor
Externí odkaz:
http://arxiv.org/abs/1807.04787
Autor:
Cambier, Léopold, Darve, Eric
Integral equations are commonly encountered when solving complex physical problems. Their discretization leads to a dense kernel matrix that is block or hierarchically low-rank. This paper proposes a new way to build a low-rank factorization of those
Externí odkaz:
http://arxiv.org/abs/1706.02812
Autor:
Chen, Chao, Cambier, Leopold, Boman, Erik G., Rajamanickam, Sivasankaran, Tuminaro, Raymond S., Darve, Eric
Publikováno v:
In Journal of Computational Physics 1 November 2019 396:819-836
