Related papers: Real-Time Data Processing in the Muon System of th…
We have implemented a cost-effective design for the readout electronics of both the anode wires and the cathode pads of large area proportional wire chambers for the HERA-B muon system based on the ASD-08 integrated circuit. To control and…
The achievable information rates of optical communication networks have been widely increased over the past four decades with the introduction and development of optical amplifiers, coherent detection, advanced modulation formats, and…
This paper introduces the first low-power hardware accelerator for Spiking Transformers, an emerging alternative to traditional artificial neural networks. By modifying the base Spikformer model to use IAND instead of residual addition, the…
A system for bunch-by-bunch detection of transverse proton and antiproton coherent oscillations in the Fermilab Tevatron collider is described. It is based on the signal from a single beam-position monitor located in a region of the ring…
In this paper an algorithm for recognizing speech has been proposed. The recognized speech is used to execute related commands which use the MFCC and two kind of classifiers, first one uses MLP and second one uses fuzzy inference system as…
The calibration procedure of a finely granulated digital hadron calorimeter with Resistive Plate Chambers as active elements is described. Results obtained with a stack of nine layers exposed to muons from the Fermilab test beam are…
Low power digital signal processors (DSPs) typically have a very limited amount of memory in which to cache data. In this paper we develop efficient bottleneck feature (BNF) extractors that can be run on a DSP, and retrain a baseline…
FPMax implements four FPUs optimized for latency or throughput workloads in two precisions, fabricated in 28nm UTBB FDSOI. Each unit's parameters, e.g pipeline stages, booth encoding etc., were optimized to yield 1.42ns latency at…
This paper presents the design and implementation of three System on Chip (SoC) cores, which implement the Digital Signal Processing (DSP) functions: Finite Impulse Response (FIR) filter, Infinite Impulse Response (IIR) filter and Fast…
In this paper, we introduce a new user-level DSM system which has the ability to directly interact with underlying interconnection networks. The DSM system provides the application programmer a flexible API to program parallel applications…
I describe recent signature-based searches for anomalous physics processes using up to 2.9/fb of data from the CDF or D0 detectors at the Fermilab Tevatron. While each search conveys its sensitivity by interpreting a null result in terms of…
Between 1992 to 1996, the CDF and D0 detectors each collected data samples exceeding 100 pb^{-1} of p\bar{p} collisions at sqrt{s}=1.8 TeV at the Fermilab Tevatron. These data sets led to a large number of precision measurements of the…
The demand for executing Deep Neural Networks (DNNs) with low latency and minimal power consumption at the edge has led to the development of advanced heterogeneous Systems-on-Chips (SoCs) that incorporate multiple specialized computing…
The rapid adaptation of data driven AI models, such as deep learning inference, training, Vision Transformers (ViTs), and other HPC applications, drives a strong need for runtime precision configurable different non linear activation…
Deploying deep neural networks (DNNs) on those resource-constrained edge platforms is hindered by their substantial computation and storage demands. Quantized multi-precision DNNs, denoted as MP-DNNs, offer a promising solution for these…
Linear data-detection algorithms that build on zero forcing (ZF) or linear minimum mean-square error (L-MMSE) equalization achieve near-optimal spectral efficiency in massive multi-user multiple-input multiple-output (MU-MIMO) systems. Such…
Deep neural networks (DNN) have shown superior performance in a variety of tasks. As they rapidly evolve, their escalating computation and memory demands make it challenging to deploy them on resource-constrained edge devices. Though…
Nonlinear effects in high-speed optical fiber systems fundamentally limit channel capacity. While traditional Digital Backward Propagation (DBP) with adaptive filters addresses these effects, its computational complexity remains…
Hyperdimensional (HD) computing involves encoding of baseline information into large hypervectors and repeated Boolean operations to generate the output class hypervectors which are stored in an associative memory. The classification task…
The Large Hadron Collider (LHC) at CERN is undergoing a major upgrade with the goal of increasing the luminosity as more statistics are needed for precision measurements. The presented work pertains to the corresponding upgrade of the ALICE…