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The Transformer Machine Learning (ML) architecture has been gaining considerable momentum in recent years. In particular, computational High-Energy Physics tasks such as jet tagging and particle track reconstruction (tracking), have either…
A 64-channel mixed-mode ASIC, suitable for particle detectors of large dynamic range and high capacitance up to hundreds of pF, is presented here. Each channel features an analogue front-end for signal amplification and filtering, and a…
The increasing complexity of transformer models in artificial intelligence expands their computational costs, memory usage, and energy consumption. Hardware acceleration tackles the ensuing challenges by designing processors and…
A Free Electron Laser (FEL) facility utilizing a recirculated Superconducting Radio Frequency (SRF) linear accelerator (linac) provides the opportunity to achieve about five times greater photon energy than an unrecirculated linac of…
We access the possibility of using the conventional RF accelerator as an injector for the plasma driven wakefield accelerator. Conventional accelerators deliver high quality beams with low emittance and low energy spread. Once injected into…
Deep learning (DL) has emerged as a rapidly developing advanced technology, enabling the performance of complex tasks involving image recognition, natural language processing, and autonomous decision-making with high levels of accuracy.…
Digital accelerators in the latest generation of CMOS processes support multiply and accumulate (MAC) operations at energy efficiencies spanning 10-to-100~fJ/Op. But the operating speed for such MAC operations are often limited to a few…
X-ray free-electron laser (XFEL) facilities require progressive compression of electron bunches as they are accelerated from an injector to the undulators. This is necessary to achieve the peak currents required for efficient lasing,…
The ATLAS Fast TracKer (FTK) was designed to provide full tracking for the ATLAS high-level trigger by using pattern recognition based on Associative Memory (AM) chips and fitting in high-speed field programmable gate arrays. The tracks…
Printed electronics technology offers a cost-effectiveand fully-customizable solution to computational needs beyondthe capabilities of traditional silicon technologies, offering ad-vantages such as on-demand manufacturing and conformal,…
The challenging conditions of the High-Luminosity LHC require tailored hardware designs for the trigger and data acquisition systems. The Apollo platform features a "Service Module" with a powerful system-on-module computer that provides…
Structure wakefield acceleration (SWFA) is one of the most promising AAC schemes in several recent strategic reports, including DOE's 2016 AAC Roadmap, report on the Advanced and Novel Accelerators for High Energy Physics Roadmap (ANAR),…
A superconducting RF accelerator test facility is being constructed at Fermilab. The existing New Muon Lab (NML) building is being converted for this facility. The accelerator will consist of an electron gun, injector, beam acceleration…
The progress of a multiple bunches of electrons through several thousand accelerator structures results in a wakefield which if left unchecked will kick successive bunches off the axis of the accelerator and can at the very least dilute the…
Given the indispensable need for a reliable network architecture to cope with 5G networks, 3GPP introduced a covet technology dubbed 5G Service Based Architecture (5G-SBA). Meanwhile, Multi-access Edge Computing (MEC) combined with SBA…
There is a growing interest in custom spatial accelerators for machine learning applications. These accelerators employ a spatial array of processing elements (PEs) interacting via custom buffer hierarchies and networks-on-chip. The…
High-brightness X-ray Free Electron Lasers (FELs) produce spatially and temporally coherent pulses on attosecond to femtosecond timescales, providing a transformative tool for discovery across biology, chemistry, physics, and materials…
High-frequency electromagnetic fields (EMFs) are increasingly recognized either as environmental risk factors or as tools for electromagnetic attacks, which are difficult to detect in situ. Existing high-frequency EMF sensors face…
Large language models (LLMs) exhibit memory-intensive behavior during decoding, making it a key bottleneck in LLM inference. To accelerate decoding execution, hybrid-bonding-based 3D-DRAM has been adopted in LLM accelerators. While this…
Convolutional Neural Networks (CNNs) serve various applications with diverse performance and resource requirements. Model-aware CNN accelerators best address these diverse requirements. These accelerators usually combine multiple dedicated…