98 citations · 971 across the 76 of their papers we have counts for
5 papers · 2 filters
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…
Python Implementation of the Dynamic Distributed Dimensional Data Model
Hayden Jananthan, Lauren Milechin, Michael Jones +17
Python has become a standard scientific computing language with fast-growing support of machine learning and data analysis modules, as well as an increasing usage of big data. The…
pPython for Parallel Python Programming
Chansup Byun, William Arcand, David Bestor +18
pPython seeks to provide a parallel capability that provides good speed-up without sacrificing the ease of programming in Python by implementing partitioned global array semantics…
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,…