Field Programmable Gate Array
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FPGA Based Feedforward System for Photonic Quantum Computing Applications
Announce Type: cross Abstract: Field-programmable gate arrays provide a high-performance solution for real-time signal processing in emerging quantum and photonic technologies. We present an FPGA-based fast feedforward system, that incorporates a high quantum efficiency fully fibre based homodyne detector, to enable low-latency signal processing critical for continuous variables (CV) measurement-based quantum information processing (MB-QIP) protocols. CV MB-QIP typically relies on adaptive...
Programming Domain-Specific FPGA Hardblocks from HLS: An RTL Blackbox Approach
Announce Type: new Abstract: Domain-specific Field Programmable Gate Array (FPGA) architectures increasingly integrate specialized hardblocks, such as Tensor Slices, to accelerate artificial intelligence and machine learning workloads. Despite their efficiency benefits, these architectures remain difficult to program because designers typically rely on manual Register-Transfer Level (RTL) integration to access these hardblocks. This paper presents a compiler-agnostic methodology that enables...
DPU or GPU for Accelerating Neural Networks Inference -- Why not both? Split CNN Inference
Announce Type: replace Abstract: Video and image streaming on edge devices requires low latency. To address this, Neural Networks (NNs) are widely used, and prior work mainly focuses on accelerating them with single hardware units such as Graphics Processing Units (GPUs), Field Programmable Gate Arrays (FPGAs), and Deep Learning Processing Units (DPUs). However, further reductions in latency can be observed by combining these units.
Ultrafast machine learning on FPGAs via Kolmogorov-Arnold Networks
Ultrafast machine learning on FPGAs via Kolmogorov-Arnold Networks This post is a high-level explainer for my Master’s thesis, which involves designing hardware architectures for ultrafast inference and online learning using the Kolmogorov-Arnold Network (KAN) architecture. I’ll assume familiarity with standard machine learning concepts, as well as some understanding of hardware and digital circuits; read my previous post here for the latter. Please read the two papers below for more...
High-bandwidth frequency domain multiplexed readout of transition-edge sensors for neutrinoless double beta decay searches
arXiv:2601.23106v3 Announce Type: replace Abstract: The next-generation of cryogenic neutrinoless double-beta decay experiments require increasingly fast readout in order to improve background discrimination. These experiments, operated as cryogenic calorimeters at $\sim$10 mK, are usually read out by high-impedance neutron transmutation doped (NTD) thermistors, which provide good energy resolution, but are limited by $\sim$1 ms response times. Superconducting detectors, such as...
Recent application studies of an INTPIX4NA SOIPIX detector-based X-ray camera using an SiTCP-XG 10GbE-based high-speed readout system at KEK facilities
arXiv:2603.09461v3 Announce Type: replace Abstract: The Silicon-On-Insulator PIXel (SOIPIX) detector is a unique monolithic structure imaging device currently being developed by the SOIPIX group, led by the High Energy Accelerator Research Organization (KEK). Our detector team at the KEK Photon Factory (PF) has developed an X-ray camera based on the INTPIX4NA SOIPIX detector. This detector provides a sensitive area of 14.1 $\times$ 8.7 $\mathrm{mm^2}$, with 425,984 pixels arranged in an...
High-bandwidth frequency domain multiplexed readout of transition-edge sensors for neutrinoless double beta decay searches
arXiv:2601.23106v2 Announce Type: replace Abstract: The next-generation of cryogenic neutrinoless double-beta decay experiments require increasingly fast readout in order to improve background discrimination. These experiments, operated as cryogenic calorimeters at $\sim$10 mK, are usually read out by high-impedance neutron transmutation doped (NTD) thermistors, which provide good energy resolution, but are limited by $\sim$1 ms response times. Superconducting detectors, such as...
Ahoy, DECmate II the little PDP-8 that could
Now, that's a lot of word processing. But under the hood it's still at least PDP-8 adjacent, even considering its oddities and incompatibilities, and you can make it do many of the things a full-size Eight can. We'll take this basic unit, convert the floppy drives to solid state, tap the video output, and put it through its paces.
A prognostic human brain network for diffuse midline glioma
Abstract Diffuse midline gliomas (DMGs) are near-universally lethal tumours of the childhood central nervous system1,2. In animal models, DMGs form brain-wide integrated networks through neuron-to-glioma synapses3,4,5,6 and glioma-to-glioma gap junctional coupling3. This extensive connectivity robustly promotes the growth and invasion of DMG3,4,5,6,7,8,9 and other glial malignancies10,11,12 through paracrine mechanisms and direct neuron-to-glioma synapses.