tag: reinforcement learning

Event-Driven RL Targets Long-Horizon Fab Control
By Technical Paper Link - 21 Jun, 2026 - Comments: 0

Researchers from Politecnico di Milano and STMicroelectronics published a technical paper titled “Event-Driven Reinforcement Learning Enables Long-Horizon Control in Semiconductor Fabrication.” The paper proposes a deep reinforcement learning framework for multi-objective policy optimization in semiconductor manufacturing, where heterogeneous wafers move through hundreds of process steps... » read more

Rethinking Robotics Reinforcement Learning: A Practical Humanoid Training Workflow
By Odin Shen - 09 Apr, 2026 - Comments: 0

Reinforcement learning (RL) for robotics is often associated with large GPU clusters, distributed infrastructure, and x86-based development environments. Training a humanoid robot with high-fidelity simulation is a resource-intensive workflow that runs in the data center. What if that workflow could run on a single workstation? In this blog post, we explore a complete robotics pipeline bu... » read more

ReRAM-based Neo-Hebbian Synapses For Training Neuromorphic HW (IIT Madras, UCSB)
By Technical Paper Link - 23 Feb, 2026 - Comments: 0

A new technical paper, "NeoHebbian synapses to accelerate online training of neuromorphic hardware," was published by researchers at IIT Madras and UC Santa Barbara. Abstract "Neuromorphic systems that employ advanced synaptic learning rules, such as the three-factor learning rule, require synaptic devices of increased complexity. Herein, a novel neoHebbian artificial synapse utilizing ReRA... » read more

AI Agents For UVM Generation: Challenges And Opportunities
By Kexun Zhang - 25 Sep, 2025 - Comments: 0

By Yuheng Tang and Kexun Zhang In the last two years, the role of AI tools in developers' workflows has rapidly expanded. What were once simple "code completion" engines have since evolved into agents that can read documentation, test their own code, and improve via self-reflection. While AI has already begun enhancing RTL design workflows, its exploration in verification remains in early st... » read more

SpiNNaker2 Neuromorphic Platform: HW-Aware Fine-Tuning of Spiking Q-Networks (TU Dresden Et Al.)
By Technical Paper Link - 05 Aug, 2025 - Comments: 0

A new technical paper titled "Hardware-Aware Fine-Tuning of Spiking Q-Networks on the SpiNNaker2 Neuromorphic Platform" was published by researchers at TU Dresden, ScaDS.AI and Centre for Tactile Internet with Human-in-the-Loop (CeTI). Excerpt "Spiking Neural Networks (SNNs) promise orders-of-magnitude lower power consumption and low-latency inference on neuromorphic hardware for a wide ran... » read more

Offline RL Framework That Dynamically Controls The GPU Clock And Server Fan Speed To Optimize Power Consumption And Computation Time (KAIST)
By Technical Paper Link - 31 May, 2025 - Comments: 0

A new technical paper titled "Power Consumption Optimization of GPU Server With Offline Reinforcement Learning" was published by researchers at Korea Advanced Institute of Science and Technology (KAIST) and KT Research and Development Center. "Optimizing GPU server power consumption is complex due to the interdependence of various components. Conventional methods often involve trade-offs: in... » read more

New Ways To Improve EDA Productivity
By Ann Mutschler - 24 Apr, 2025 - Comments: 0

EDA vendors are taking aim at new ways to improve the productivity of design and verification engineers, who are struggling to keep pace with exponential increases in chip complexity in tight time-to-market windows and with constrained engineering talent pipelines. In the past, progress often was as straightforward as improving algorithms or parallelizing computations in a linear flow. But w... » read more

Cache Coherence In Network On Chip Design (NTU)
By Technical Paper Link - 08 Apr, 2025 - Comments: 0

A new technical paper titled "Learning Cache Coherence Traffic for NoC Routing Design" was published by researchers at Nanyang Technological University. "In this work, we propose a cache coherence-aware routing approach with integrated topology selection, guided by our Cache Coherence Traffic Analyzer (CCTA). Our method achieves up to 10.52% lower packet latency, 55.51% faster execution time... » read more

DeepSeek: Improving Language Model Reasoning Capabilities Using Pure Reinforcement Learning
By Technical Paper Link - 27 Jan, 2025 - Comments: 0

A new technical paper titled "DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning" was published by DeepSeek. Abstract: "We introduce our first-generation reasoning models, DeepSeek-R1-Zero and DeepSeek-R1. DeepSeek-R1-Zero, a model trained via large-scale reinforcement learning (RL) without supervised fine-tuning (SFT) as a preliminary step, demonstrates rema... » read more

The Impact Of ML On Chip Design
By Ed Sperling - 22 May, 2023 - Comments: 0

Node scaling and rising complexity are increasing the time it takes to get chips out the door. At the same time, design teams are not getting larger. What is needed is a way to automate the creative process, and to not have to start every design from scratch. This is where reinforcement learning fits in, with its ability to centralize and store “tribal knowledge. Thomas Andersen, vice preside... » read more

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