9 citations · 20 across the 9 of their papers we have counts for
7 papers · 1 filter
To Push or To Pull: On Reducing Communication and Synchronization in Graph Computations
Maciej Besta, Michal Podstawski, Linus Groner +2
We reduce the cost of communication and synchronization in graph processing by analyzing the fastest way to process graphs: pushing the updates to a shared state or pulling the upd…
Efficient parallel CP decomposition with pairwise perturbation and multi-sweep dimension tree
Linjian Ma, Edgar Solomonik
CP tensor decomposition with alternating least squares (ALS) is dominated in cost by the matricized-tensor times Khatri-Rao product (MTTKRP) kernel that is necessary to set up the…
SlimSell: A Vectorizable Graph Representation for Breadth-First Search
Maciej Besta, Florian Marending, Edgar Solomonik +1
Vectorization and GPUs will profoundly change graph processing. Traditional graph algorithms tuned for 32- or 64-bit based memory accesses will be inefficient on architectures with…
Distributed-Memory DMRG via Sparse and Dense Parallel Tensor Contractions
Ryan Levy, Edgar Solomonik, Bryan K. Clark
The Density Matrix Renormalization Group (DMRG) algorithm is a powerful tool for solving eigenvalue problems to model quantum systems. DMRG relies on tensor contractions and dense…
Efficient 2D Tensor Network Simulation of Quantum Systems
Yuchen Pang, Tianyi Hao, Annika Dugad +2
Simulation of quantum systems is challenging due to the exponential size of the state space. Tensor networks provide a systematically improvable approximation for quantum states. 2…
AutoHOOT: Automatic High-Order Optimization for Tensors
Linjian Ma, Jiayu Ye, Edgar Solomonik
High-order optimization methods, including Newton's method and its variants as well as alternating minimization methods, dominate the optimization algorithms for tensor decompositi…