Paper Info
Title
ISAVS: interactive scalable analysis and visualization system.
Abstract
Modern science is inundated with ever increasing data sizes as computational capabilities and image acquisition techniques continue to improve. For example, simulations are tackling ever larger domains with higher fidelity, and high-throughput microscopy techniques generate larger data that are fundamental to gather biologically and medically relevant insights. As the image sizes exceed memory, and even sometimes local disk space, each step in a scientific workflow is impacted. Current software solutions enable data exploration with limited interactivity for visualization and analytic tasks. Furthermore analysis on HPC systems often require complex hand-written parallel implementations of algorithms that suffer from poor portability and maintainability. We present a software infrastructure that simplifies end-to-end visualization and analysis of massive data. First, a hierarchical streaming data access layer enables interactive exploration of remote data, with fast data fetching to test analytics on subsets of the data. Second, a library simplifies the process of developing new analytics algorithms, allowing users to rapidly prototype new approaches and deploy them in an HPC setting. Third, a scalable runtime system automates mapping analysis algorithms to whatever computational hardware is available, reducing the complexity of developing scaling algorithms. We demonstrate the usability and performance of our system using a use case from neuroscience: filtering, registration, and visualization of tera-scale microscopy data. We evaluate the performance of our system using a leadership-class supercomputer, Shaheen II.
Year
DOI
Venue
2017
10.1145/3139295.3139299
SA '17: SIGGRAPH Asia 2017 Bangkok Thailand November, 2017
Keywords
Field
DocType
Computing methodologies → Massively parallel algorithms,Integrated and visual development environments,Interactive visualization and analysis,Parallel programming languages,Software and its engineering → Development frameworks and environments,algorithms scalability,microscopy,parallel custom analysis work-flows
Computer graphics (images),Computer science,Visualization,Software,Software portability,Data access layer,Analytics,Workflow,Scalability,Runtime system
Conference
Volume
ISBN
Citations 
2017
978-1-4503-5411-0
1
PageRank 
References 
Authors
0.37
7
8
Name
Order
Citations
PageRank
Steve Petruzza133.79
Aniketh Venkat211.05
Attila Gyulassy345323.11
Giorgio Scorzelli41377.38
Frederick Federer510.71
Alessandra Angelucci6101.85
Valerio Pascucci73241192.33
P.-T. Bremer822.08