Aravind Sukumaran-Rajam

TDC: Towards Extremely Efficient CNNs on GPUs via Hardware-Aware Tucker Decomposition

Tucker decomposition is one of the SOTA CNN model compression techniques. However, unlike the FLOPs reduction, we observe very limited inference time reduction with Tucker-compressed models using...

Analytical Characterization and Design Space Exploration for Optimization of CNNs

Moving data through the memory hierarchy is a fundamental bottleneck that can limit the performance of core algorithms of machine learning, such as convolutional neural networks (CNNs). Loop-level...

Load-Balanced Sparse MTTKRP on GPUs

Sparse matricized tensor times Khatri-Rao product (MTTKRP) is one of the most computationally expensive kernels in sparse tensor computations. This work focuses on optimizing the MTTKRP operation...

Efficient distributed algorithms for Convolutional Neural Networks

Several efficient distributed algorithms have been developed for matrix-matrix multiplication: the 3D algorithm, the 2D SUMMA algorithm, and the 2.5D algorithm. Each of these algorithms was...

PL-NMF: Parallel Locality-Optimized Non-negative Matrix Factorization

Non-negative Matrix Factorization (NMF) is a key kernel for unsupervised dimension reduction used in a wide range of applications, including topic modeling, recommender systems and bioinformatics....

On Optimizing Complex Stencils on GPUs

A Performance Portability Study Using Tensor Contraction Benchmarks

Effective Machine Learning Based Format Selection and Performance Modeling for SpMV on GPUs

Speculative Runtime Parallelization of Loop Nests: Towards Greater Scope and Efficiency

Sparsity-Aware Tensor Decomposition

TTLG - An Efficient Tensor Transposition Library for GPUs

Load-Balanced Sparse MTTKRP on GPUs

Communication Optimization for Distributed Execution of Graph Neural Networks

Parallel CCD++ on GPU for Matrix Factorization

Register optimizations for stencils on GPUs

Adaptive sparse tiling for sparse matrix multiplication

Performance modeling for GPUs using abstract kernel emulation

Online Dynamic Dependence Analysis for Speculative Polyhedral Parallelization