Publications (20)
GNNerator: A Hardware/Software Framework for Accelerating Graph Neural Networks
Jacob R. Stevens, Dipankar Das, Sasikanth Avancha +2
AI Powered Compiler Techniques for DL Code Optimization
Sanket Tavarageri, Gagandeep Goyal, Sasikanth Avancha +2
On Scale-out Deep Learning Training for Cloud and HPC
Srinivas Sridharan, Karthikeyan Vaidyanathan, Dhiraj Kalamkar +8
RAIL: Risk-Averse Imitation Learning
Anirban Santara, Abhishek Naik, Balaraman Ravindran +4
High Performance Scalable FPGA Accelerator for Deep Neural Networks
Sudarshan Srinivasan, Pradeep Janedula, Saurabh Dhoble +7
Hierarchical Block Sparse Neural Networks
Dharma Teja Vooturi, Dheevatsa Mudigere, Sasikanth Avancha
Anatomy Of High-Performance Deep Learning Convolutions On SIMD Architectures
Evangelos Georganas, Sasikanth Avancha, Kunal Banerjee +4
Hardware Acceleration of Sparse and Irregular Tensor Computations of ML Models: A Survey and Insights
Shail Dave, Riyadh Baghdadi, Tony Nowatzki +3
High-Performance Deep Learning via a Single Building Block
Evangelos Georganas, Kunal Banerjee, Dhiraj Kalamkar +6
Generative Active Learning for the Search of Small-molecule Protein Binders
Maksym Korablyov, Cheng-Hao Liu, Moksh Jain +31
SEERL: Sample Efficient Ensemble Reinforcement Learning
Rohan Saphal, Balaraman Ravindran, Dheevatsa Mudigere +2
Mixed Precision Training of Convolutional Neural Networks using Integer Operations
Dipankar Das, Naveen Mellempudi, Dheevatsa Mudigere +14
DistGNN-MB: Distributed Large-Scale Graph Neural Network Training on x86 via Minibatch Sampling
Md Vasimuddin, Ramanarayan Mohanty, Sanchit Misra +1
Tensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning & HPC Workloads
Evangelos Georganas, Dhiraj Kalamkar, Sasikanth Avancha +16
A Study of BFLOAT16 for Deep Learning Training
Dhiraj Kalamkar, Dheevatsa Mudigere, Naveen Mellempudi +16
Distributed Deep Learning Using Synchronous Stochastic Gradient Descent
Dipankar Das, Sasikanth Avancha, Dheevatsa Mudigere +5
PolyDL: Polyhedral Optimizations for Creation of High Performance DL primitives
Sanket Tavarageri, Alexander Heinecke, Sasikanth Avancha +3
Deep Graph Library Optimizations for Intel(R) x86 Architecture
Sasikanth Avancha, Vasimuddin Md, Sanchit Misra +1
DistGNN: Scalable Distributed Training for Large-Scale Graph Neural Networks
Vasimuddin Md, Sanchit Misra, Guixiang Ma +6
PolyScientist: Automatic Loop Transformations Combined with Microkernels for Optimization of Deep Learning Primitives
Sanket Tavarageri, Alexander Heinecke, Sasikanth Avancha +3