Design Space ExecutionLucy Nowell
Design Space Execution Program
Beyond the Standard Model
ExecModelsThomas Sterling, Kevin Barker
Evaluating Exascale Execution Models
Modeling Execution Models
The next-generation of scientific discovery will be enabled by research developments that can effectively harness significant or disruptive advances...
Whole-program Adaptive Error Detection and Mitigation
CatalogChristian Englemann, Martin Schulz, Franck Cappello
Characterizing Faults, Errors, and Failures in Extreme-scale Systems
HMDR&SA William Kramer
Holistic Measurement Driven Resilience: Combining Operational Fault and Failure Measurements and Fault Injection for Quantifying Fault Detection and...
The Scientific Data Management and Analysis at Extreme Scale program funds innovative basic research in computer science for management and analysis...
The goal of the CODES project is to use highly parallel simulation to explore the design of exascale storage architectures and distributed data-...
Supporting Co-Design of Extreme-Scale Systems with In Situ Visual Analysis of Event-Driven Simulations
Adding Data Management Services to Parallel File Systems
This project will create a fundamental shift in the design and development of tools for next-generation scientific data by focusing on efficiency...
Scalable, In-situ Data Clustering Data Analysis for Extreme Scale Scientific Computing
ECRP: Data Exploration at the Exascale
ECRP: Combating the Data Movement Bottleneck
A Pervasive Parallel Processing Framework for Data Visualization and Analysis at Extreme Scale
DecafTom Peterka, Prabhat Prabhat
High Performance Decoupling of Tightly-Coupled Data Flows
Extreme-Scale Distribution-Based Data Analysis
An I/O Platform for Exascale Data Models, Analysis and Performance
ECRP: Efficient graph kernels for extreme scale analysis of environmental community data
This project focuses on a key set of problems facing our community as we move towards the exascale regime and respond to challenges resulting from...
IDEALS: Improving Data Exploration and Analysis at Large Scale
ECRP: Images Across Domains, Experiments, Algorithms and Learning
An Information-Theoretic Framework for Enabling Extreme-Scale Science Discovery
In situ Indexing and Query Processing of AMR Data
Exploration of Exascale In Situ Visualization and Analysis Approaches
Performance Understanding and Analysis for Exascale Data Management Workflows
Dynamic Non-Hierarchical File Systems for Exascale Storage
OptEnergyCogJames Ahrens, David Rogers
Optimizing the Energy Usage and Cognitive Value of Extreme Scale Data Analysis Approaches
Optimizing Power Usage for Data-Intensive Workflows and Algorithms on Modern Computing Architectures
Runtime System for I/O Staging in Support of In-Situ Processing of Extreme Scale Data
ScalableKDWes Bethel, Gunther Weber, Venkatram Vishwanath, Patrick O'Leary, Matthew Wolf, Earl Duque, Dmitriy Morozov, John Wu, Brad Whitlock, Utkarsh Ayachit, Greg Eisenhauer, Nicola Ferrier
Scalable Analysis Methods and In Situ Infrastructure for Extreme Scale Knowledge Discovery
Domain-Specific Languages for in situ Data Analysis and Visualization on Emerging Architectures
Scientific Data Management in the Exascale Era
Scientific Data Services (SDS) – Autonomous Data Management on Exascale Infrastructure
ECRP: Scalable and Energy-Efficient Methods for Interactive Exploration of Scientific Data
Towards Exascale: High Performance Visualization and Analytics
Usable Data Abstractions for Next-Generation Scientific Workflows
A Unified Data-Driven Approach for Programming In Situ Analysis and Visualization
Scalable and Power Efficient Data Analytics for Hybrid Exascale Systems
XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem
The processing capability of computing systems, especially supercomputers, continues to increase rapidly. Within 10 years, exascale platforms will...
Modeling Impacts of Resilience Architectures for Extreme-Scale Storage Systems
HolisticIONicholas Wright, Phil Carns, Suren Byna
A Framework for Holistic I/O Workload Characterization
A Software Defined Storage Approach to Exascale Storage Services
The X-Stack Program conducts basic research that represents significant advances in programming models, languages, compilers, runtime systems and...
Motivation High performance scientific computing Exascale: O(106) nodes, O(103) cores per node Requires asynchrony and “relaxed” memory consistency...
Domain Specific Languages (DSLs) are a tranformational technology that capture expert knowledge about applica@on domains. For the domain scientist,...
Mission Statement: To ensure the broad success of Exascale systems through a unified programming model that is productive, scalable, portable, and...
This project will conduct research on runtime software for exascale computing. Moving forward, exascale software will be unable to rely on minimally...
Fault-oblivious Extreme-scale Execution Environment
Application Partnerships Advanced Nuclear Reactor Simulation (Andrew Siegel, CESAR) Computational Chemistry (Jeff Hammond, ALCF) Rich Computational...
This project is developing new techniques for measuring, analyzing, attributing, and presenting performance data on exascale systems. Objectives...
Motivations Modern computational science applications composed of many different libraries Computational libraries, communication libraries, data...
Goal: Research and mature software technologies addressing major Exascale challenges and get ready to intercept by 2018-2020 Objectives: Energy...
What is Autotuning? Definition: Automatically generate a “search space” of possible implementations of a computation A code variant represents a...
Goals, Objectives, and Approach Goals: Enable exascale performance capability for current and future DOE applications Develop and deliver a practical...