Uncovering Instabilities In Variational-Quantum Deep Q-Networks

By Maja Franz (1), Lucas Wolf (1), Maniraman Periyasamy (2), Christian Ufrecht (2), Daniel D. Scherer (2), Axel Plinge (2), Christopher Mutschler (2), Wolfgang Mauerer (1,3) (1) Technical University of Applied Sciences, Regensburg, Germany, (2) Fraunhofer-IIS, Fraunhofer Institute for Integrated Circuits IIS, Division Positioning and Networks, Nuremberg, Germany, (3) Siemens AG, Corporate ... » read more

More Efficient Matrix-Multiplication Algorithms with Reinforcement Learning (DeepMind)

A new research paper titled "Discovering faster matrix multiplication algorithms with reinforcement learning" was published by researchers at DeepMind. "Here we report a deep reinforcement learning approach based on AlphaZero for discovering efficient and provably correct algorithms for the multiplication of arbitrary matrices," states the paper. Find the technical paper link here. Publis... » read more

Deep Reinforcement Learning to Dynamically Configure NoC Resources

New research paper titled "Deep Reinforcement Learning Enabled Self-Configurable Networks-on-Chip for High-Performance and Energy-Efficient Computing Systems" from Md Farhadur Reza at Eastern Illinois University. Find the open access technical paper here. Published June 2022. M. F. Reza, "Deep Reinforcement Learning Enabled Self-Configurable Networks-on-Chip for High-Performance and Energ... » read more

A graph placement methodology for fast chip design

Abstract "Chip floorplanning is the engineering task of designing the physical layout of a computer chip. Despite five decades of research1, chip floorplanning has defied automation, requiring months of intense effort by physical design engineers to produce manufacturable layouts. Here we present a deep reinforcement learning approach to chip floorplanning. In under six hours, our method autom... » read more

System Bits: Nov. 6

Keeping data private To preserve privacy during data collection from the Internet, Stanford University researchers have developed a new technique that maintains personal privacy given that the many devices part of our daily lives collect information about how we use them. Stanford computer scientists Dan Boneh and Henry Corrigan-Gibbs created the Prio method for keeping collected data priva... » read more