Naifeng Zhang

According to our database, Naifeng Zhang authored at least 9 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Faster Game Solving via Hyperparameter Schedules.

Naifeng Zhang, Stephen McAleer, Tuomas Sandholm

CoRR, 2024

2023

RPU: The Ring Processing Unit.

Deepraj Soni, Negar Neda, Naifeng Zhang, Benedict Reynwar, Homer Gamil, Benjamin Heyman, Mohammed Thari Nabeel, Ahmad Al Badawi, Yuriy Polyakov, Kellie Canida, Massoud Pedram, Michail Maniatakos, David Bruce Cousins, Franz Franchetti, Matthew French, Andrew G. Schmidt, Brandon Reagen

IACR Cryptol. ePrint Arch., 2023

TREBUCHET: Fully Homomorphic Encryption Accelerator for Deep Computation.

David Bruce Cousins, Yuriy Polyakov, Ahmad Al Badawi, Matthew French, Andrew G. Schmidt, Ajey P. Jacob, Benedict Reynwar, Kellie Canida, Akhilesh R. Jaiswal, Clynn Mathew, Homer Gamil, Negar Neda, Deepraj Soni, Michail Maniatakos, Brandon Reagen, Naifeng Zhang, Franz Franchetti, Patrick Brinich, Jeremy Johnson, Patrick Broderick, Mike Franusich, Bo Zhang, Zeming Cheng, Massoud Pedram

IACR Cryptol. ePrint Arch., 2023

Generating High-Performance Number Theoretic Transform Implementations for Vector Architectures.

Naifeng Zhang, Austin Ebel, Negar Neda, Patrick Brinich, Benedict Reynwar, Andrew G. Schmidt, Mike Franusich, Jeremy Johnson, Brandon Reagen, Franz Franchetti

Proceedings of the IEEE High Performance Extreme Computing Conference, 2023

Optimization and Performance Analysis of Shor's Algorithm in Qiskit.

Dewang Sun, Naifeng Zhang, Franz Franchetti

Proceedings of the IEEE High Performance Extreme Computing Conference, 2023

2022

Towards the shortest DRAT proof of the Pigeonhole Principle.

Isaac Grosof, Naifeng Zhang, Marijn J. H. Heule

CoRR, 2022

2021

GenMAT: A General-Purpose Machine Learning-Driven Auto-Tuner for Heterogeneous Platforms.

Naifeng Zhang, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna

Proceedings of the IEEE/ACM Programming Environments for Heterogeneous Computing, 2021

2020

Compiler Abstractions and Runtime for Extreme-scale SAR and CFD Workloads.

Connor Imes, Alexei Colin, Naifeng Zhang, Ajitesh Srivastava, Viktor K. Prasanna, John Paul Walters

Proceedings of the 5th IEEE/ACM International Workshop on Extreme Scale Programming Models and Middleware, 2020

Towards High Performance, Portability, and Productivity: Lightweight Augmented Neural Networks for Performance Prediction.

Ajitesh Srivastava, Naifeng Zhang, Rajgopal Kannan, Viktor K. Prasanna

Proceedings of the 27th IEEE International Conference on High Performance Computing, 2020