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Found 5 papers, 2 papers with code
MCR-DL: Mix-and-Match Communication Runtime for Deep Learning
However, such distributed DL parallelism strategies require a varied mixture of collective and point-to-point communication operations across a broad range of message sizes and scales.
Shisha: Online scheduling of CNN pipelines on heterogeneous architectures
Shisha targets heterogeneity in compute performance and memory bandwidth and tunes the pipeline schedule through a fast online exploration technique.
Extreme Scale FMM-Accelerated Boundary Integral Equation Solver for Wave Scattering
With distributed memory optimizations, on the other hand, we report near-optimal efficiency in the weak scalability study with respect to both the logarithmic communication complexity as well as the theoretical scaling complexity of FMM.
Performance Computational Engineering, Finance, and Science Mathematical Software
Asynchronous Execution of the Fast Multipole Method Using Charm++
Fast multipole methods (FMM) on distributed mem- ory have traditionally used a bulk-synchronous model of com- municating the local essential tree (LET) and overlapping it with computation of the local data.
Distributed, Parallel, and Cluster Computing 70F10 D.1.2; D.1.3; G.1.0; G.1.2
Adaptive Graph via Multiple Kernel Learning for Nonnegative Matrix Factorization
In this paper, we propose a novel idea which engages a Multiple Kernel Learning approach into refining the graph structure that reflects the factorization of the matrix and the new data space.
