33 citations · 95 across the 12 of their papers we have counts for
12 papers
Union: An Automatic Workload Manager for Accelerating Network Simulation
Xin Wang, Misbah Mubarak, Yao Kang +2
With the rapid growth of the machine learning applications, the workloads of future HPC systems are anticipated to be a mix of scientific simulation, big data analytics, and machin…
HPC Storage Service Autotuning Using Variational-Autoencoder-Guided Asynchronous Bayesian Optimization
Matthieu Dorier, Romain Egele, Prasanna Balaprakash +5
Distributed data storage services tailored to specific applications have grown popular in the high-performance computing (HPC) community as a way to address I/O and storage challen…
A Case Study on Parallel HDF5 Dataset Concatenation for High Energy Physics Data Analysis
Sunwoo Lee, Kai-yuan Hou, Kewei Wang +8
In High Energy Physics (HEP), experimentalists generate large volumes of data that, when analyzed, helps us better understand the fundamental particles and their interactions. This…
A Taxonomy of Error Sources in HPC I/O Machine Learning Models
Mihailo Isakov, Mikaela Currier, Eliakin del Rosario +6
I/O efficiency is crucial to productivity in scientific computing, but the increasing complexity of the system and the applications makes it difficult for practitioners to understa…
A Visual Analytics Framework for Reviewing Streaming Performance Data
Suraj P. Kesavan, Takanori Fujiwara, Jianping Kelvin Li +5
Understanding and tuning the performance of extreme-scale parallel computing systems demands a streaming approach due to the computational cost of applying offline algorithms to va…
Improving MPI Collective I/O Performance With Intra-node Request Aggregation
Qiao Kang, Sunwoo Lee, Kai-yuan Hou +4
Two-phase I/O is a well-known strategy for implementing collective MPI-IO functions. It redistributes I/O requests among the calling processes into a form that minimizes the file a…