Software Engineering Institute | Carnegie Mellon University
Software Engineering Institute | Carnegie Mellon University

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Scott McMillan
October 2017 - Presentation Measuring Performance of Big Learning Workloads

Authors: Scott McMillan

Presentation on research to build a performance measurement workbench with tools to measure and report performance of large-scale ML platforms

October 2017 - Presentation Automated Code Generation for High-Performance Graph Libraries

Authors: Scott McMillan

Presentation on research into graph analytics

October 2017 - Poster Measuring Performance of Big Learning Workloads

Authors: Scott McMillan

Poster on research to build a performance measurement workbench with tools to measure and report performance of large-scale ML platforms

October 2017 - Poster Automated Code Generation for High-Performance, Future-Compatible Graph Libraries

Authors: Scott McMillan

Poster on research into graph analytics

October 2017 - Poster Automated Code Generation for High-Performance, Future-Compatible Graph Libraries (2017)

Authors: Scott McMillan

Poster for research project on graph analytics

November 2016 - Presentation GraphBLAS: A Programming Specification for Graph Analysis

Authors: Scott McMillan

Describes work in graph analysis, an important and pervasive areas for the DoD

October 2016 - Poster GraphBLAS

Authors: Scott McMillan

A Programming Specification for Graph Analysis

July 2016 - Presentation Design and Implementation of the GraphBLAS Template Library (GBTL)

Authors: Scott McMillan, Samantha Misurda, Marcin Zalewski (Indiana University), Peter Zhang (Indiana University), Andrew Lumsdaine (Indiana University)

The design of the GraphBLAS Template Library separates graph algorithm development from performance tuning for heterogeneous high-performance computing architectures.

May 2016 - Conference Paper GBTL-CUDA: Graph Algorithms and Primitives for GPUs

Authors: Peter Zhang (Indiana University), Marcin Zalewski (Indiana University), Andrew Lumsdaine (Indiana University), Samantha Misurda, Scott McMillan

In this paper we present our initial implementation of GraphBLAS primitives for graphics processing unit (GPU) systems called GraphBLAS Template Library (GBTL).

December 2015 - Conference Paper Dynamic Parallelism for Simple and Efficient GPU Graph Algorithms

Authors: Peter Zhang (Indiana University), Eric Holk (Indiana University), John Matty, Samantha Misurda, Marcin Zalewski (Indiana University), Jonathan Chu, Scott McMillan, Andrew Lumsdaine (Indiana University)

Presented at the 2015 Supercomputing Conference, this paper shows that dynamic parallelism enables relatively high-performance graph algorithms for GPUs.

October 2015 - Poster Graph Algorithms on Future Architectures Poster (SEI 2015 Research Review)

Authors: Scott McMillan

Delves into whether primitives and operations can be defined to separate graph analytic application development and complexity of underlying hardware concern

October 2015 - Presentation Graph Algorithms on Future Architectures

Authors: Scott McMillan

Delves into whether primitives and operations can be defined to separate graph analytic application development and complexity of underlying hardware concern

August 2015 - Podcast Toward Speed and Simplicity: Creating a Software Library for Graph Analytics

Topics: Cyber-Physical Systems

Authors: Scott McMillan, Eric Werner

In this podcast, Scott McMillan and Eric Werner of the SEI's Emerging Technology Center discuss work to create a software library for graph analytics that would take advantage of more powerful heterogeneous supercomputers.

August 2014 - Technical Note Patterns and Practices for Future Architectures

Topics: Ultra-Large-Scale Systems

Authors: Eric Werner, Scott McMillan, Jonathan Chu

This report discusses best practices and patterns that will make high-performance graph analytics on new and emerging architectures more accessible to users.