Publications
MagmaDNN 0.2 High-Performance Data Analytics for Manycore GPUs and CPUs
: University of Tennessee, January 2019.
DOI: 10.13140/RG.2.2.14906.64961 (7.84 MB)
MAGMA Tensors and Batched Computing for Accelerating Applications on GPUs
, San Jose, CA, GPU Technology Conference (GTC17), Presentation in Session S7728, May 2017.
(11.12 MB)
MAGMA MIC: Optimizing Linear Algebra for Intel Xeon Phi
, Frankfurt, Germany, ISC High Performance (ISC15), Intel Booth Presentation, June 2015.
(2.03 MB)
MAGMA MIC: Linear Algebra Library for Intel Xeon Phi Coprocessors
, Salt Lake City, UT, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC12), November 2012.
(6.4 MB)
MAGMA - LAPACK for HPC on Heterogeneous Architectures
, Oak Ridge, TN, Titan Summit at Oak Ridge National Laboratory, Presentation, August 2011.
(20.43 MB)
MAGMA - LAPACK for GPUs
, Atlanta, GA, Keeneland GPU Tutorial, April 2011.
(742.14 KB)
MAGMA: A New Generation of Linear Algebra Library for GPU and Multicore Architectures
, Salt Lake City, UT, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC12), Presentation, November 2012.
(4.69 MB)
MAGMA: A Breakthrough in Solvers for Eigenvalue Problems
, San Jose, CA, GPU Technology Conference (GTC12), Presentation, May 2012.
(9.23 MB)
Linear Algebra Software for High-Performance Computing (Part 2: Software for Hardware Accelerators and Coprocessors)
, Frankfurt, Germany, ISC High Performance (ISC18), Tutorial Presentation, June 2015.
(15.41 MB)
Linear Algebra Prepara.on for Emergent Neural Network Architectures: MAGMA, BLAS, and Batched GPU Computing
, Virtual, LAPENNA Workshop, November 2021.
(17.8 MB)
An Introduction to the MAGMA project - Acceleration of Dense Linear Algebra
: NVIDIA Webinar, June 2010.
Integrating Deep Learning in Domain Science at Exascale (MagmaDNN)
, virtual, DOD HPCMP seminar, December 2020.
(11.12 MB)
How to Build Your Own Deep Neural Network
: PEARC20, July 2020.
(18.8 MB)
The Future of Computing: Software Libraries
, Savannah, GA, DOD CREATE Developers' Review, Keynote Presentation, February 2012.
(6.76 MB)
Dense Linear Algebra Solvers for Multicore with GPU Accelerators
, Atlanta, GA, International Parallel and Distributed Processing Symposium (IPDPS 2010), April 2010.
(956.68 KB)
Autotuning Dense Linear Algebra Libraries on GPUs
, Basel, Switzerland, Sixth International Workshop on Parallel Matrix Algorithms and Applications (PMAA 2010), June 2010.
(579.44 KB)
Accelerating Tensor Contractions in High-Order FEM with MAGMA Batched
, Atlanta, GA, SIAM Conference on Computer Science and Engineering (SIAM CSE17), Presentation, March 2017.
(9.29 MB)
Accelerating Linear Algebra with MAGMA
, Knoxville, TN, ECP Annual Meeting 2018, Tutorial, February 2018.
(35.27 MB)
Accelerating Linear Algebra on Heterogeneous Architectures of Multicore and GPUs using MAGMA and DPLASMA and StarPU Schedulers
: 2010 Symposium on Application Accelerators in. High-Performance Computing (SAAHPC'10), Tutorial, July 2010.
(499.51 KB)
hipMAGMA v2.0
: Zenodo, July 2020.
DOI: 10.5281/zenodo.3928667
hipMAGMA v1.0
: Zenodo, March 2020.
DOI: 10.5281/zenodo.3908549
Using GPU FP16 Tensor Cores Arithmetic to Accelerate Mixed-Precision Iterative Refinement Solvers and Reduce Energy Consumption
, Frankfurt, Germany, ISC High Performance (ISC18), Best Poster Award, June 2018.
(3.01 MB)
Towards a High-Performance Tensor Algebra Package for Accelerators
, Gatlinburg, TN, moky Mountains Computational Sciences and Engineering Conference (SMC15), September 2015.
(1.76 MB)
Tensor Contractions using Optimized Batch GEMM Routines
, San Jose, CA, GPU Technology Conference (GTC), Poster, March 2018.
(1.64 MB)
A Standard for Batched BLAS Routines
, Paris, France, 17th SIAM Conference on Parallel Processing for Scientific Computing (SIAM PP16), April 2016.
(1.93 MB)
Scheduling Cholesky Factorization on Multicore Architectures with GPU Accelerators
, Knoxville, TN, 2010 Symposium on Application Accelerators in High-Performance Computing (SAAHPC'10), Poster, July 2010.
(3.86 MB)
Power-aware Computing on GPGPUs
, Gatlinburg, TN, Fall Creek Falls Conference, Poster, September 2011.
(2.89 MB)
Optimizing Batch HGEMM on Small Sizes Using Tensor Cores
, San Jose, CA, GPU Technology Conference (GTC), March 2019.
(2.47 MB)
Numerical Linear Algebra on Hybrid Architectures: Recent Developments in the MAGMA Project
, Portland, Oregon, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC09), November 2009.
(1.41 MB)
Numerical Linear Algebra on Emerging Architectures: The PLASMA and MAGMA Projects
, Portland, OR, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC09), November 2009.
(3.53 MB)
MAtrix, TEnsor, and Deep-learning Optimized Routines (MATEDOR)
, Washington, DC, NSF PI Meeting, Poster, April 2018.
DOI: 10.6084/m9.figshare.6174143.v3 (2.4 MB)
MATEDOR: MAtrix, TEnsor, and Deep-learning Optimized Routines
, Dallas, TX, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC18), Research Poster, November 2018.
(2.55 MB)
MATEDOR: MAtrix, TEnsor, and Deep-learning Optimized Routines
, Seattle, WA, 2020 NSF Cyberinfrastructure for Sustained Scientific Innovation (CSSI) Principal Investigator Meeting, February 2020.
(2.28 MB)
heFFTe: Highly Efficient FFT for Exascale (Poster)
, Houston, TX, 2020 Exascale Computing Project Annual Meeting, February 2020.
(6.2 MB)
heFFTe: Highly Efficient FFT for Exascale (Poster)
: NVIDIA GPU Technology Conference (GTC2020), October 2020.
(866.88 KB)
heFFTe: Highly Efficient FFT for Exascale (Poster)
, Seattle, WA, SIAM Conference on Parallel Processing for Scientific Computing (SIAM PP20), February 2020.
(1.54 MB)
Harnessing GPU's Tensor Cores Fast FP16 Arithmetic to Speedup Mixed-Precision Iterative Refinement Solvers and Achieve 74 Gflops/Watt on Nvidia V100
, San Jose, CA, GPU Technology Conference (GTC), Poster, March 2018.
(2.96 MB)
GPUDirect MPI Communications and Optimizations to Accelerate FFTs on Exascale Systems,”
EuroMPI'19 Posters, Zurich, Switzerland, no. icl-ut-19-06: ICL, September 2019.
(2.25 MB)
“FFT-ECP Fast Fourier Transform
, Houston, TX, 2019 ECP Annual Meeting (Research Poster), January 2019.
(1.51 MB)
Extending MAGMA Portability with OneAPI
, Dallas, TX, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC22), ACM Student Research Competition, November 2022.
(1.33 MB)
Enhancing the Performance of Dense Linear Algebra Solvers on GPUs (in the MAGMA Project)
, Austin, TX, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC08), November 2008.
(5.28 MB)
Clover: Computational Libraries Optimized via Exascale Research
, Houston, TX, 2020 Exascale Computing Project Annual Meeting, February 2020.
(872 KB)
Cholesky Factorization on Batches of Matrices with Fixed and Variable Sizes
, San Jose, CA, GPU Technology Conference (GTC16), Poster, April 2016.
(480.51 KB)
Acceleration of the BLAST Hydro Code on GPU,”
Supercomputing '12 (poster), Salt Lake City, Utah, SC12, November 2012.
“Accelerating Tensor Contractions for High-Order FEM on CPUs, GPUs, and KNLs
, Gatlinburg, TN, moky Mountains Computational Sciences and Engineering Conference (SMC16), Poster, September 2016.
(4.29 MB)
Accelerating FFT towards Exascale Computing
: NVIDIA GPU Technology Conference (GTC2021), 2021.
(27.23 MB)
Accelerating 2D FFT: Exploit GPU Tensor Cores through Mixed-Precision
, Dallas, TX, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC18), ACM Student Research Poster, November 2018.
(740.37 KB)
With Extreme Computing, the Rules Have Changed,”
Computing in Science & Engineering, vol. 19, issue 3, pp. 52-62, May 2017.
DOI: 10.1109/MCSE.2017.48 (485.34 KB)
“Using Mixed Precision for Sparse Matrix Computations to Enhance the Performance while Achieving 64-bit Accuracy,”
ACM Transactions on Mathematical Software, vol. 34, no. 4, pp. 17-22, 00 2008.
(364.48 KB)
“Using MAGMA with PGI Fortran,”
PGI Insider, November 2010.
(176.67 KB)
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