Publications

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

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  • 178 results found

2023

NVCell 2: Routability-Driven Standard Cell Layout in Advanced Nodes with Lattice Graph Routability Model
Chia-Tung (Mark) Ho, Alvin Ho, Matt Fojtik, Minsoo Kim, Shang Wei, Yaguang LI, Brucek Khailany, Mark Haoxing Ren
AutoDMP: Automated DREAMPlace-based Macro Placement
Anthony Agnesina, Puranjay Rajvanshi, Tian Yang, Geraldo Pradipta, Austin Jiao, Ben Keller, Brucek Khailany, Mark Haoxing Ren
On Legalization of Die Bonding Bumps and Pads for 3D ICs
Sai Pentapati, Anthony Agnesina, Moritz Brunion, Yen-Hsiang Huang, Sung Kyu Lim
Joint Neural Denoising of Surfaces and Volumes
Nikolai Hofmann, Jon Hasselgren, Jacob Munkberg
FreeNeRF: Improving Few-shot Neural Rendering with Free Frequency Regularization
Heng Yang, Marco Pavone
Equivariant Architectures for Learning in Deep Weight Spaces
Aviv Navon, Aviv Shamsian, Idan Achituve, Ethan Fetaya, Gal Chechik, Haggai Maron
Visibility Algorithms for Dynamic Dependence Analysis and Distributed Coherence
Michael Bauer, Elliott Slaughter, Sean Treichler, Wonchan Lee, Michael Garland, Alex Aiken
Parsimony: Enabling SIMD/Vector Programming in Standard Compiler Flows
Vijay Kandiah, Daniel Lustig, Oreste Villa, David Nellans, Nikos Hardavellas
Enabling Scalable AI Computational Lithography with Physics-Inspired Models
Haoyu Yang, Mark Haoxing Ren
Beyond CPO: A Motivation and Approach for Bringing Optics onto the Silicon Interposer
Ben Lee, Nikola Nedovic, Trey Greer, Tom Gray
Target-free Text-guided Image Manipulation
Wan-Cyuan Fan, Cheng-Fu Yang, Chiao-An Yang, Frank Wang
Frido: Feature Pyramid Diffusion for Complex Scene Image Synthesis
Wan-Cyuan Fan, Yen-Chun Chen, Dongdong Chen, Yu Cheng, Lu Yuan, Frank Wang
Implementing Reinforcement Learning Datacenter Congestion Control in NVIDIA NICs
Benjamin Fuhrer, Yuval Shpigelman, Chen Tessler, Shie Mannor, Gal Chechik, Eitan Zahavy, Gal Dalal
A 95.6-TOPS/W Deep Learning Inference Accelerator With Per-Vector Scaled 4-bit Quantization in 5 nm
Ben Keller, Rangharajan Venkatesan, Steve Dai, Stephen Tell, Brian Zimmer, Charbel Sakr, William Dally, Tom Gray, Brucek Khailany
BufFormer: A Generative ML Framework for Scalable Buffering
Rongjian Liang, Siddhartha Nath, Anand Rajaram, Jiang Hu, Mark Haoxing Ren
Efficient Dataflow Modeling of Peripheral Encoding in the Human Visual System
Rachel Brown, Vasha DuTell, Bruce Walter, Ruth Rosenholtz, Peter Shirley, Morgan McGuire, David Luebke
Never Worse, Mostly Better: Stable Policy Improvement in Deep Reinforcement Learning
Pranav Khanna, Guy Tennenholtz, Nadav Merlis, Shie Mannor, Chen Tessler
Self-Supervised Pyramid Representation Learning for Multi-Label Visual Analysis and Beyond
Cheng-Yen Hsieh, Chih-Jung Chang, Fu-En Yang, Frank Wang