Chiplet-Based NPUs to Accelerate Vehicular AI Perception Workloads


A new technical paper titled "Performance Implications of Multi-Chiplet Neural Processing Units on Autonomous Driving Perception" was published by researchers at UC Irvine. Abstract "We study the application of emerging chiplet-based Neural Processing Units to accelerate vehicular AI perception workloads in constrained automotive settings. The motivation stems from how chiplets technology i... » read more

STCO for Dense Edge Architectures using 3D Integration and NVM (imec,, et al.)


A new technical paper titled "System-Technology Co-Optimization for Dense Edge Architectures using 3D Integration and Non-Volatile Memory" was published by researchers at imec, INESC-ID, Université Libre de Bruxelles, et al. "In this paper, we present an system-technology co-optimization (STCO) framework that interfaces with workload-driven system scaling challenges and physical design-enab... » read more

Critical Design Considerations For High-Bandwidth Chiplet Interconnects (TSMC)


A new technical paper titled "High-Bandwidth Chiplet Interconnects for Advanced Packaging Technologies in AI/ML Applications: Challenges and Solutions" was published by researchers at TSMC. Abstract: "The demand for chiplet integration using 2.5D and 3D advanced packaging technologies has surged, driven by the exponential growth in computing performance required by Artificial Intelligence a... » read more

Pooling CPU Memory for LLM Inference With Lower Latency and Higher Throughput (UC Berkeley)


A new technical paper titled "Pie: Pooling CPU Memory for LLM Inference" was published by researchers at UC Berkeley. Abstract "The rapid growth of LLMs has revolutionized natural language processing and AI analysis, but their increasing size and memory demands present significant challenges. A common solution is to spill over to CPU memory; however, traditional GPU-CPU memory swapping ofte... » read more

Backpropagation Algorithm On Neuromorphic Spiking HW (U. Of Zurich, ETH Zurich, LANL)


A new technical paper titled "The backpropagation algorithm implemented on spiking neuromorphic hardware" was published by University of Zurich, ETH Zurich, Los Alamos National Laboratory, Royal Institution, London, et al. "This study presents a neuromorphic, spiking backpropagation algorithm based on synfire-gated dynamical information coordination and processing implemented on Intel’s Lo... » read more

Dedicated 3D Accelerator Specifically Designed For Emerging Spiking Transformers


A new technical paper titled "Spiking Transformer Hardware Accelerators in 3D Integration" was published by researchers at UC Santa Barbara, Georgia Tech and Burapha University. "Recognizing the current lack of dedicated hardware support for spiking transformers, this paper presents the first work on 3D spiking transformer hardware architecture and design methodology. We present an architect... » read more

Workload-Specific Data Movements Across AI Workloads in Multi-Chiplet AI Accelerators


A new technical paper titled "Communication Characterization of AI Workloads for Large-scale Multi-chiplet Accelerators" was published by researchers at Universitat Politecnica de Catalunya. Abstract "Next-generation artificial intelligence (AI) workloads are posing challenges of scalability and robustness in terms of execution time due to their intrinsic evolving data-intensive characteris... » read more

Benchmark and Evaluation Framework For Characterizing LLM Performance In Formal Verification (UC Berkeley, Nvidia)


A new technical paper titled "FVEval: Understanding Language Model Capabilities in Formal Verification of Digital Hardware" was published by researchers at UC Berkeley and NVIDIA. Abstract "The remarkable reasoning and code generation capabilities of large language models (LLMs) have spurred significant interest in applying LLMs to enable task automation in digital chip design. In particula... » read more

Current and Emerging Heterogeneous Integration Technologies For High-Performance Systems (Georgia Tech)


A technical paper titled "Heterogeneous Integration Technologies for Artificial Intelligence Applications" was published by Georgia Tech. Abstract "The rapid advancement of artificial intelligence (AI) has been enabled by semiconductor-based electronics. However, the conventional methods of transistor scaling are not enough to meet the exponential demand for computing power driven by AI. ... » read more

Survey: HW SW Co-Design Approaches Tailored to LLMs


A new technical paper titled "A Survey: Collaborative Hardware and Software Design in the Era of Large Language Models" was published by researchers at Duke University and Johns Hopkins University. Abstract "The rapid development of large language models (LLMs) has significantly transformed the field of artificial intelligence, demonstrating remarkable capabilities in natural language proce... » read more

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