tag: LLM

HW-based Heterogeneous Memory Management for LLM Inferencing (KAIST, Stanford Unversity)
By Technical Paper Link - 22 Apr, 2025 - Comments: 0

A new technical paper titled "Hardware-based Heterogeneous Memory Management for Large Language Model Inference" was published by researchers at KAIST and Stanford University. Abstract "A large language model (LLM) is one of the most important emerging machine learning applications nowadays. However, due to its huge model size and runtime increase of the memory footprint, LLM inferences suf... » read more

LLM-based Agentic Framework Automating HW Security Threat Modeling And Test Plan Generation (U. of Florida)
By Technical Paper Link - 01 Apr, 2025 - Comments: 0

A new technical paper titled "ThreatLens: LLM-guided Threat Modeling and Test Plan Generation for Hardware Security Verification" was published by researchers at University of Florida. Abstract "Current hardware security verification processes predominantly rely on manual threat modeling and test plan generation, which are labor-intensive, error-prone, and struggle to scale with increasing ... » read more

Wafer-Scale Computing for LLMs (U. of Edinburgh, Microsoft)
By Technical Paper Link - 09 Feb, 2025 - Comments: 0

A new technical paper titled "WaferLLM: A Wafer-Scale LLM Inference System" was published by researchers at University of Edinburgh and Microsoft Research. Abstract "Emerging AI accelerators increasingly adopt wafer-scale manufacturing technologies, integrating hundreds of thousands of AI cores in a mesh-based architecture with large distributed on-chip memory (tens of GB in total) and ultr... » read more

Pooling CPU Memory for LLM Inference With Lower Latency and Higher Throughput (UC Berkeley)
By Technical Paper Link - 26 Nov, 2024 - Comments: 0

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

Language’s Role In Embodied Agents
By Ben Gomes - 27 Jun, 2024 - Comments: 0

Large Language Models (LLMs) and models cross-trained on natural language are a major growth area for edge applications of neural networks and Artificial Intelligence (AI). Within the spectrum of applications, embodied agents stand out as a major developing focal point for this AI. This article will address developments in this space and how the application of language-trained models improves t... » read more

Generative AI On Mobile Is Running On The Arm CPU
By Adnan Al-Sinan - 15 Feb, 2024 - Comments: 0

By Adnan Al-Sinan and Gian Marco Iodice 2023 was the year that showcased an impressive number of use cases powered by generative AI. This disruptive form of artificial intelligence (AI) technology is at the heart OpenAI's ChatGPT and Google’s Gemini AI model, with it demonstrating the opportunity to simplify work and advance education through generating text, images, or even audio content ... » read more

LLM Inference On CPUs (Intel)
By Technical Paper Link - 16 Nov, 2023 - Comments: 0

A technical paper titled “Efficient LLM Inference on CPUs” was published by researchers at Intel. Abstract: "Large language models (LLMs) have demonstrated remarkable performance and tremendous potential across a wide range of tasks. However, deploying these models has been challenging due to the astronomical amount of model parameters, which requires a demand for large memory capacity an... » read more

Applications Of Large Language Models For Industrial Chip Design (NVIDIA)
By Technical Paper Link - 10 Nov, 2023 - Comments: 0

A technical paper titled “ChipNeMo: Domain-Adapted LLMs for Chip Design” was published by researchers at NVIDIA. Abstract: "ChipNeMo aims to explore the applications of large language models (LLMs) for industrial chip design. Instead of directly deploying off-the-shelf commercial or open-source LLMs, we instead adopt the following domain adaptation techniques: custom tokenizers, domain-ad... » read more

GNN-Based Pre-Silicon Power Side-Channel Analysis Framework At RTL Level
By Technical Paper Link - 16 Oct, 2023 - Comments: 0

A technical paper titled “SCAR: Power Side-Channel Analysis at RTL-Level” was published by researchers at University of Texas at Dallas, Technology Innovation Institute and University of Illinois Chicago. Abstract: "Power side-channel attacks exploit the dynamic power consumption of cryptographic operations to leak sensitive information of encryption hardware. Therefore, it is necessary t... » read more

Partitioning Processors For AI Workloads
By Ann Mutschler - 12 Oct, 2023 - Comments: 0

Partitioning in complex chips is beginning to resemble a high-stakes guessing game, where choices need to extrapolate from what is known today to what is expected by the time a chip finally ships. Partitioning of workloads used to be a straightforward task, although not necessarily a simple one. It depended on how a device was expected to be used, the various compute, storage and data paths ... » read more

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