Publications

Our publications provide insight into some of our leading-edge research.

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2020

DREAMPlace: Deep Learning Toolkit-Enabled GPU Acceleration for Modern VLSI Placement
Yibo Lin, Zixuan Jiang, Jiaqi Gu, Wuxi Li, Shounak Dhar, Haoxing (Mark) Ren, Brucek Khailany, David Z. Pan
2021 IEEE Transactions on Computer-Aided Design Donald O. Pederson Best Paper Award
Monte Carlo Gradient Quantization
Goncalo Mordido, Matthijs Van keirsbilck, Alex Keller
ABCDPlace: Accelerated Batch-based Concurrent Detailed Placement on Multi-threaded CPUs and GPUs
Yibo Lin, Wuxi Li, Jiaqi Gu, Haoxing (Mark) Ren, Brucek Khailany, David Z. Pan

2019

Instant Quantization of neural networks using Monte Carlo Methods
Gonçalo Mordido, Matthijs Van keirsbilck, Alex Keller
DREAMPlace: Deep Learning Toolkit-Enabled GPU Acceleration for Modern VLSI Placement
Yibo Lin, Shounak Dhar, Wuxi Li, Haoxing (Mark) Ren, Brucek Khailany, David Z. Pan
DAC 2019 Best Paper Award
Dynamic Diffuse Global Illumination with Ray-Traced Irradiance Fields
Zander Majercik, Jean-Philippe Guertin, Derek Nowrouzezahrai, Morgan McGuire
Cool Patches: A Geometric Approach to Ray/Bilinear Patch Intersections
Alexander Reshetov
Rethinking full connectivity in recurrent neural networks
Matthijs Van keirsbilck, Alex Keller, Xiaodong Yang
A Fast and Robust Method for Avoiding Self-Intersection
Carsten Wächter, Nikolaus Binder
Massively Parallel Path Space Filtering
Nikolaus Binder, Sascha Fricke, Alex Keller
Massively Parallel Construction of Radix Tree Forests for the Efficient Sampling of Discrete Probability Distributions
Nikolaus Binder, Alex Keller

2018

Fast, High Precision Ray/Fiber Intersection using Tight, Disjoint Bounding Volumes
Nikolaus Binder, Alex Keller
Massively Parallel Stackless Ray Tracing of Catmull-Clark Subdivision Surfaces
Nikolaus Binder, Alex Keller
Machine Learning and Rendering
Alex Keller, Jaroslav Křivánek, Jan Novák, Anton Kaplanyan, Marco Salvi
Phantom Ray-Hair Intersector
Alexander Reshetov, David Luebke

2017

Parallel Complexity of Forward and Backward Propagation
Maxim Naumov
Integral Equations and Machine Learning
Alex Keller, Ken Dahm
AdaBatch: Adaptive Batch Sizes for Training Deep Neural Networks
Aditya Devarakonda, Maxim Naumov, Michael Garland
Near-eye Light Field Holographic Rendering with Spherical Waves for Wide Field of View Interactive 3D Computer Graphics
Liang Shi, Fu-Chung Huang, Ward Lopes, Wojciech Matusik, David Luebke
Low Communication FMM-Accelerated FFT on GPUs
Cris Cecka
Parallel Jaccard and Related Graph Clustering Techniques
Alexandre Fender, Nahid Emad, Serge Petiton, Joe Eaton, Maxim Naumov
Spatiotemporal Variance-Guided Filtering: Real-Time Reconstruction for Path-Traced Global Illumination
Christoph Schied, Anton Kaplanyan, Chris Wyman, Anjul Patney, Chakravarty R. Alla Chaitanya, John Burgess, Shiqiu Liu, Carsten Dachsbacher, Aaron Lefohn, Marco Salvi
Exploiting Budan-Fourier and Vincent’s Theorems for Ray Tracing 3D Bézier Curves
Alexander Reshetov
Generating stratified random lines in a square
Peter Shirley, Chris Wyman
Parallel Modularity Clustering
Alexandre Fender, Nahid Emad, Serge Petiton, Maxim Naumov
The Iray Light Transport Simulation and Rendering System
Alex Keller, Carsten Wächter, Matthias Raab, Daniel Seibert, Dietger van Antwerpen, Johann Korndörfer, Lutz Kettner
Learning Light Transport the Reinforced Way
Ken Dahm, Alex Keller

2016

GI next: global illumination for production rendering on GPUs
Enzo Catalano, Rajko Yasui-Schöffel , Ken Dahm, Nikolaus Binder, Alex Keller
Exploring and Expanding the Continuum of OIT Algorithms
Chris Wyman
Efficient stackless hierarchy traversal on GPUs with backtracking in constant time
Nikolaus Binder, Alex Keller
Hybrid Modulation for Near Zero Display Latency
Trey Greer, Josef Spjut, David Luebke, Turner Whitted
S-Step and Communication-Avoiding Iterative Methods
Maxim Naumov