tag: TPUs

AI Accelerators Usher In New Era For IC Test
By Laura Peters - 07 Apr, 2026 - Comments: 0

Key Takeaways The parallelism in AI accelerators enables low latency but complicates failure isolation. HBM can account for 50% of package cost, so known-good stack assurance is critical. DFT and test cooperate to solve final test, singulated die test, SLT, and in-system test for data centers. AI accelerators are used for everything from training large language models to mak... » read more

MIT’s Survey On Accelerators and Processors for Inference, With Peak Performance And Power Comparisons
By Technical Paper Link - 31 Oct, 2025 - Comments: 0

A new technical paper titled "Lincoln AI Computing Survey (LAICS) and Trends" was published by researchers at MIT Lincoln Laboratory Supercomputing Center. Abstract "In the past year, generative AI (GenAI) models have received a tremendous amount of attention, which in turn has increased attention to computing systems for training and inference for GenAI. Hence, an update to this survey is ... » read more

Server-Scale Programmable Photonic Fabric to Interconnect Accelerators Within Servers (Cornell University, Lightmatter)
By Technical Paper Link - 15 Aug, 2025 - Comments: 0

A new technical paper titled "Morphlux: Programmable chip-to-chip photonic fabrics in multi-accelerator servers for ML" was published by researchers at Cornell University and Lightmatter. Abstract "We optically interconnect accelerator chips (e.g., GPUs, TPUs) within compute servers using newly viable programmable chip-to-chip photonic fabrics. In contrast, today, commercial multi-accelerat... » read more

LLM Inference: Core Bottlenecks Imposed By Memory, Compute Capacity, Synchronization Overheads (NVIDIA)
By Technical Paper Link - 01 Aug, 2025 - Comments: 0

A new technical paper titled "Efficient LLM Inference: Bandwidth, Compute, Synchronization, and Capacity are all you need" was published by NVIDIA. Abstract "This paper presents a limit study of transformer-based large language model (LLM) inference, focusing on the fundamental performance bottlenecks imposed by memory bandwidth, memory capacity, and synchronization overhead in distributed ... » read more

Cradle-To-Grave Analysis Of The Carbon Footprint of AI Hardware (Google)
By Technical Paper Link - 24 Feb, 2025 - Comments: 0

A new technical paper titled "Life-Cycle Emissions of AI Hardware: A Cradle-To-Grave Approach and Generational Trends" was published by researchers at Google. Abstract "Specialized hardware accelerators aid the rapid advancement of artificial intelligence (AI), and their efficiency impacts AI's environmental sustainability. This study presents the first publication of a comprehensive AI acc... » read more

Survey: HW SW Co-Design Approaches Tailored to LLMs
By Technical Paper Link - 11 Oct, 2024 - Comments: 0

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

Data Formats For Inference On The Edge
By Brian Bailey - 14 Dec, 2023 - Comments: 0

AI/ML training traditionally has been performed using floating point data formats, primarily because that is what was available. But this usually isn't a viable option for inference on the edge, where more compact data formats are needed to reduce area and power. Compact data formats use less space, which is important in edge devices, but the bigger concern is the power needed to move around... » read more

Complex Tradeoffs In Inferencing Chips
By John Koon - 17 Oct, 2022 - Comments: 0

Designing AI/ML inferencing chips is emerging as a huge challenge due to the variety of applications and the highly specific power and performance needs for each of them. Put simply, one size does not fit all, and not all applications can afford a custom design. For example, in retail store tracking, it's acceptable to have a 5% or 10% margin of error for customers passing by a certain aisle... » read more

New Uses For AI In Chips
By John Koon and Ed Sperling - 11 Aug, 2022 - Comments: 1

Artificial intelligence is being deployed across a number of new applications, from improving performance and reducing power in a wide range of end devices to spotting irregularities in data movement for security reasons. While most people are familiar with using machine learning and deep learning to distinguish between cats and dogs, emerging applications show how this capability can be use... » read more

Toward Democratized IC Design And Customized Computing
By Jason Cong - 28 Jun, 2022 - Comments: 0

Integrated circuit (IC) design is often considered a “black art,” restricted to only those with advanced degrees or years of training in electrical engineering. Given that the semiconductor industry is struggling to expand its workforce, IC design must be rendered more accessible. The benefit of customized computing General-purpose computers are widely used, but their performance improv... » read more

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