72 citations · 346 across the 20 of their papers we have counts for
9 papers · 1 filter
Toward Sustainable HPC: Carbon Footprint Estimation and Environmental Implications of HPC Systems
Baolin Li, Rohan Basu Roy, Daniel Wang +3
The rapid growth in demand for HPC systems has led to a rise in carbon footprint, which requires urgent intervention. In this work, we present a comprehensive analysis of the carbo…
Clover: Toward Sustainable AI with Carbon-Aware Machine Learning Inference Service
Baolin Li, Siddharth Samsi, Vijay Gadepally +1
This paper presents a solution to the challenge of mitigating carbon emissions from hosting large-scale machine learning (ML) inference services. ML inference is critical to modern…
KAIROS: Building Cost-Efficient Machine Learning Inference Systems with Heterogeneous Cloud Resources
Baolin Li, Siddharth Samsi, Vijay Gadepally +1
Online inference is becoming a key service product for many businesses, deployed in cloud platforms to meet customer demands. Despite their revenue-generation capability, these ser…
RIBBON: Cost-Effective and QoS-Aware Deep Learning Model Inference using a Diverse Pool of Cloud Computing Instances
Baolin Li, Rohan Basu Roy, Tirthak Patel +3
Deep learning model inference is a key service in many businesses and scientific discovery processes. This paper introduces RIBBON, a novel deep learning inference serving system t…
MISO: Exploiting Multi-Instance GPU Capability on Multi-Tenant Systems for Machine Learning
Baolin Li, Tirthak Patel, Siddarth Samsi +2
GPU technology has been improving at an expedited pace in terms of size and performance, empowering HPC and AI/ML researchers to advance the scientific discovery process. However,…
The MIT Supercloud Workload Classification Challenge
Benny J. Tang, Qiqi Chen, Matthew L. Weiss +24
High-Performance Computing (HPC) centers and cloud providers support an increasingly diverse set of applications on heterogenous hardware. As Artificial Intelligence (AI) and Machi…
The MIT Supercloud Dataset
Siddharth Samsi, Matthew L Weiss, David Bestor +24
Artificial intelligence (AI) and Machine learning (ML) workloads are an increasingly larger share of the compute workloads in traditional High-Performance Computing (HPC) centers a…
Two stage cluster for resource optimization with Apache Mesos
Gourav Rattihalli, Pankaj Saha, Madhusudhan Govindaraju +1
As resource estimation for jobs is difficult, users often overestimate their requirements. Both commercial clouds and academic campus clusters suffer from low resource utilization…
Measuring and Managing Answer Quality for Online Data-Intensive Services
Jaimie Kelley, Christopher Stewart, Nathaniel Morris +3
Online data-intensive services parallelize query execution across distributed software components. Interactive response time is a priority, so online query executions return answer…