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Found 13 papers, 0 papers with code
The MIT Supercloud Workload Classification Challenge
We introduce a labelled dataset that can be used to develop new approaches to workload classification and present initial results based on existing approaches.
The MIT Supercloud Dataset
In this paper we introduce the MIT Supercloud Dataset which aims to foster innovative AI/ML approaches to the analysis of large scale HPC and datacenter/cloud operations.
Mathematics of Digital Hyperspace
The GraphBLAS standard currently supports hypergraphs, hypersparse matrices, the mathematics required for semilinks, and seamlessly performs graph, network, and matrix operations.
Accuracy and Performance Comparison of Video Action Recognition Approaches
Over the past few years, there has been significant interest in video action recognition systems and models.
Benchmarking network fabrics for data distributed training of deep neural networks
The large computational requirements for training deep models have necessitated the development of new methods for faster training.
GraphChallenge.org Sparse Deep Neural Network Performance
The Sparse Deep Neural Network (DNN) Challenge draws upon prior challenges from machine learning, high performance computing, and visual analytics to create a challenge that is reflective of emerging sparse AI systems.
Sparse Deep Neural Network Graph Challenge
The Sparse DNN Challenge is based on a mathematically well-defined DNN inference computation and can be implemented in any programming environment.
Securing HPC using Federated Authentication
Federated authentication can drastically reduce the overhead of basic account maintenance while simultaneously improving overall system security.
Distributed, Parallel, and Cluster Computing Cryptography and Security
Streaming 1.9 Billion Hypersparse Network Updates per Second with D4M
This work describes the design and performance optimization of an implementation of hierarchical associative arrays that reduces memory pressure and dramatically increases the update rate into an associative array.
A Billion Updates per Second Using 30,000 Hierarchical In-Memory D4M Databases
Streaming updates to a large associative array requires a hierarchical implementation to optimize the performance of the memory hierarchy.
Databases Distributed, Parallel, and Cluster Computing Data Structures and Algorithms Networking and Internet Architecture
Training Behavior of Sparse Neural Network Topologies
We test pruning-based topologies, which are derived from an initially dense network whose connections are pruned, as well as RadiX-Nets, a class of network topologies with proven connectivity and sparsity properties.
Sparse Deep Neural Network Exact Solutions
This work uses associative array DNNs to construct exact solutions and corresponding perturbation models to the rectified linear unit (ReLU) DNN equations that can be used to construct test vectors for sparse DNN implementations over various precisions.
Benchmarking Data Analysis and Machine Learning Applications on the Intel KNL Many-Core Processor
Thus, the performance of these applications on KNL systems is of high interest to LLSC users and the broader data analysis and machine learning communities.
Performance Instrumentation and Methods for Astrophysics Distributed, Parallel, and Cluster Computing Computational Physics
