Application Specific Integrated Circuits for High Resolution X and Gamma Ray Semiconductor Detectors

The increasing demand for performance improvements in radiation detectors, driven by cutting-edge research in nuclear physics, astrophysics and medical imaging, is causing not only a proliferation in the variety of the radiation sensors, but also a growing necessity of tailored solutions for the front-end readout electronics. Within this work, novel solutions for application specific integrated circuits (ASICs) adopted in high-resolution X and $$\upgamma $$ γ ray spectroscopy applications are studied. In the first part of this work, an ultra-low noise charge sensitive amplifier (CSA) is presented, with specific focus on sub-microsecond filtering, addressing the growing interest in high-luminosity experiments. The CSA demonstrated excellent results with Silicon Drift Detectors (SDDs), and with room temperature Cadmium-Telluride (CdTe) detectors, recording a state-of-the-art noise performance. The integration of the CSA within two full-custom radiation detection instruments realized for the ELETTRA (Trieste, Italy) and SESAME (Allan, Jordan) synchrotrons is also presented. In the second part of this work, an ASIC constellation designed for X-Gamma imaging spectrometer (XGIS) onboard of the THESEUS space mission is described. The presented readout ASIC has a highly customized distributed architecture, and integrates a complete on-chip signal filtering, acquisition and digitization with an ultra-low power consumption.

Evaluation of Green Alternatives for Blockchain Proof-of-Work (PoW) Approach

Following the footprints of Bitcoins, many other cryptocurrencies were developed mostly adopting the same or similar Proof-of-Work (PoW) approach. Since completing the PoW puzzle requires extremely high computing power, consuming a vast amount of electricity, PoW has been strongly criticised for its antithetic stand against the notion of green computing. Use of application-specific hardware, particularly application-specific integrated circuits (ASICs) has further fuelled the debate, as these devices are of no use once they become “legacy” and hence obsolete to compete in the mining race, thus contributing to electronics waste. Therefore, this paper surveys the currently available alternative approaches to PoW and evaluates their applicability - especially their appropriateness in terms of greenness.

The first family of application-specific integrated circuits for programmable metasurfaces

Reconfigurable metasurfaces are man-made surfaces, which consist of sub-wavelength periodic elements - meta-atoms - that can be reconfigured to manipulate incoming electromagnetic waves. However, reconfigurable metasurfaces developed to-date, have limitations in terms of impedance range, reconfiguration delay and power consumption. Also, these systems are costly and they require bulky electronics and complex control circuits, which makes them unattractive for commercial use. Here, we report the first family of CMOS application-specific integrated circuits (ASICs) that enable microsecond and microwatt reconfiguration of complex impedances at microwave frequencies. Our approach utilizes asynchronous digital control circuitry, with networking capabilities, allowing simple and fast reconfiguration via digital devices and user-friendly software. Our solution is low-cost and can cover arbitrary metasurfaces, with different sizes and shapes.

Implementation of FPGA accelerator architecture for Convolution Neural Network in Emotional Recognition System

The field of deep learning, artificial intelligence has arisen due to the later advancements in computerized innovation and the accessibility of data information, has exhibited its ability and adequacy in taking care of complex issues in learning that were not previously conceivable. The viability in emotional detection and acknowledging specific applications have demonstrated by Convolution neural networks (CNNs). In any case, concentrated Processor activities and memory transfer speed are necessitated that cause general CPUs to neglect to accomplish the ideal degrees of execution. Subsequently, to build the throughput of CNNs, equipment quickening agents utilizing General Processing Units (GPUs), Field Programmable Gate Array (FPGAs) and Application Specific Integrated circuits (ASICs) has been used. We feature the primary highlights utilized for productivity improving by various techniques for speeding up. Likewise, we offer rules to upgrade the utilization of FPGAs for the speeding up of CNNs. The proposed algorithm on to an FPGA platform and show that emotions recognition utterance duration 1.5s is identified in 1.75ms, while utilizing 75% of the resources. This further demonstrates the suitability of our approach for real-time applications on Emotional Recognition system.

FPGAs in Client Compute Hardware

<div>Field-programmable gate arrays (FPGAs) are remarkably versatile. FPGAs are used in a wide variety of applications and industries where use of application-specific integrated circuits (ASICs) is less economically feasible. Despite the area, cost, and power challenges designers face when integrating FPGAs into devices, they provide significant security and performance benefits. Many of these benefits can be realized in client compute hardware such as laptops, tablets, and smartphones.</div>

FPGAs in Client Compute Hardware

<div>Field-programmable gate arrays (FPGAs) are remarkably versatile. FPGAs are used in a wide variety of applications and industries where use of application-specific integrated circuits (ASICs) is less economically feasible. Despite the area, cost, and power challenges designers face when integrating FPGAs into devices, they provide significant security and performance benefits. Many of these benefits can be realized in client compute hardware such as laptops, tablets, and smartphones.</div>

FPGAs in Client Compute Hardware

<div>Field-programmable gate arrays (FPGAs) are remarkably versatile. FPGAs are used in a wide variety of applications and industries where use of application-specific integrated circuits (ASICs) is less economically feasible. Despite the area, cost, and power challenges designers face when integrating FPGAs into devices, they provide significant security and performance benefits. Many of these benefits can be realized in client compute hardware such as laptops, tablets, and smartphones.</div>