[PDF][PDF] Cross-System Analysis of Job Characterization and Scheduling in Large-Scale Computing Clusters
Amid the growing prevalence of artificial intelligence (AI) and deep learning (DL) across
industries and science disciplines, high-performance computing (HPC) clusters are …
industries and science disciplines, high-performance computing (HPC) clusters are …
[PDF][PDF] Hadar: Heterogeneity-Aware Optimization-Based Online Scheduling for Deep Learning Cluster
With the wide adoption of deep neural network (DNN) models for various applications,
enterprises, and cloud providers have built deep learning clusters and increasingly …
enterprises, and cloud providers have built deep learning clusters and increasingly …
[PDF][PDF] Dissecting I/O Burstiness in Machine Learning Cloud Platform: A Case Study on Alibaba's MLaaS
With advancements in machine learning (ML) technology and the availability of large ML-as-
a-Service (MLaaS) clouds, accurately understanding the I/O behaviors in the storage …
a-Service (MLaaS) clouds, accurately understanding the I/O behaviors in the storage …
[PDF][PDF] Optimizing Resource Management for Machine Learning Workloads in High-Performance Clusters
Resource management and job scheduling are the key to high-performance computing
(HPC) clusters for high system utilization, short user wait time, and fair resource allocation …
(HPC) clusters for high system utilization, short user wait time, and fair resource allocation …
[PDF][PDF] ASSIST-IoT Technical Report# 13
Federated learning (FL) was proposed to facilitate the training of models in a distributed
environment. It supports the protection of (local) data privacy and uses local resources for …
environment. It supports the protection of (local) data privacy and uses local resources for …