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

Digital Library

Scott McMillan
October 2018 - Poster Building a COTS Benchmark Baseline for Graph Analytics

Authors: Scott McMillan

This poster describes research aimed at building a benchmark baseline based on commercial off-the-shelf (COTS) field-programmable gate array (FPGA) hardware.

October 2018 - Poster Automatic Code Generation for Graph Algorithms

This poster describes automated code generation of high-performance libraries of graph algorithms, tuned for different hardware architectures.

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)

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

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

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

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

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