Improving GPU Energy Efficiency With Component-Level Power Management (AMD)


Researchers from AMD released “CompPow: A Case for Component-level GPU Power Management”. Abstract “The ever increasing demand for ML-driven intelligence in a wide spectrum of domains has led to ubiquity of GPUs. At the same time, GPUs are notorious for their power consumption needs and often dominate power allocation in a typical ML datacenter. While datacenter-level power opti... » read more

Hardware Deployment for Secure AI Using Confidential Computing


AI’s fast evolution is producing autonomous systems that can operate with minimal human oversight, improve themselves and become effective at decision-making in complex environments. These developments require careful consideration of security and privacy. To limit the overhead performance impact (area, throughput, latency and power), hardware-based security solutions can be deploye... » read more

RPU: A Chiplet-Based Architecture To Address The Challenges of the Modern Memory Wall (Harvard University)


Researchers from Harvard University have released “RPU -- A Reasoning Processing Unit”. Abstract “Large language model (LLM) inference performance is increasingly bottlenecked by the memory wall. While GPUs continue to scale raw compute throughput, they struggle to deliver scalable performance for memory bandwidth bound workloads. This challenge is amplified by emerging reasonin... » read more

Survey of GenAI Across the Full Computing Stack, From SW To Silicon (Harvard)


Harvard University researchers published "GenAI for Systems: Recurring Challenges and Design Principles from Software to Silicon." Abstract "Generative AI is reshaping how computing systems are designed, optimized, and built, yet research remains fragmented across software, architecture, and chip design communities. This paper takes a cross-stack perspective, examining how generative models... » read more

Multi-Core Architecture Optimized For Time-Predictable Neural Network Inference (FZI, KIT)


A new technical paper titled "MultiVic: A Time-Predictable RISC-V Multi-Core Processor Optimized for Neural Network Inference" was published by researchers at FZI Research Center for Information Technology and Karlsruhe Institute for Information Technology (KIT). Abstract: "Real-time systems, particularly those used in domains like automated driving, are increasingly adopting neural network... » read more

Leveraging Multi-Agent RL for Microprocessor Design Space (Harvard, Google)


A new technical paper titled "Multi-Agent Reinforcement Learning for Microprocessor Design Space Exploration" was published by researchers at Harvard University and Google research groups. Abstract "Microprocessor architects are increasingly resorting to domain-specific customization in the quest for high-performance and energy-efficiency. As the systems grow in complexity, fine-tuning arch... » read more

Convolutional Neural Networks: Co-Design of Hardware Architecture and Compression Algorithm


Researchers at Soongsil University (Korea) published "A Survey on Efficient Convolutional Neural Networks and Hardware Acceleration." Abstract: "Over the past decade, deep-learning-based representations have demonstrated remarkable performance in academia and industry. The learning capability of convolutional neural networks (CNNs) originates from a combination of various feature extraction... » read more

Advances In Reconfigurable Intelligent Surfaces Hardware Architectures: Beyond 5G/6G


This technical paper titled "Reconfigurable Intelligent Surfaces for Wireless Communications: Overview of Hardware Designs, Channel Models, and Estimation Techniques" is from researchers at IEEE. The paper's abstract states "we overview and taxonomize the latest advances in RIS [reconfigurable intelligent surfaces] hardware architectures as well as the most recent developments in the modelin... » read more

A Safety-Oriented System Hardware Architecture Exploration Framework


New technical paper titled "Safety-Oriented System Hardware Architecture Exploration in Compliance with ISO 26262" from researchers at National Taipei University. Abstract: "Safety-critical intelligent automotive systems require stringent dependability while the systems are in operation. Therefore, safety and reliability issues must be addressed in the development of such safety-critical sy... » read more

MIT: Stackable AI Chip With Lego-style Design


New technical paper titled "Reconfigurable heterogeneous integration using stackable chips with embedded artificial intelligence" from researchers at MIT, along with Harvard University, Tsinghua University, Zhejiang University, and others. Partial Abstract: "Here we report stackable hetero-integrated chips that use optoelectronic device arrays for chip-to-chip communication and neuromorphic... » read more

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