IRIDE:Interdisciplinary research infrastructure based on dual electron linacs and lasers

This paper describes the scientific aims and potentials as well as the preliminary technical design of IRIDE, an innovative tool for multi-disciplinary investigations in a wide field of scientific, technological and industrial applications. IRIDE will be a high intensity "particles factory", based on a combination of high duty cycle radio-frequency superconducting electron linacs and of high energy lasers. Conceived to provide unique research possibilities for particle physics, for condensed matter physics, chemistry and material science, for structural biology and industrial applications, IRIDE will open completely new research possibilities and advance our knowledge in many branches of science and technology. IRIDE is also supposed to be realized in subsequent stages of development depending on the assigned priorities. © 2013 Elsevier B.V.

A Significance-Driven Programming Framework for Energy-Constrained Approximate Computing

Approximate execution is a viable technique for energy-con\-strained environments, provided that applications have the mechanisms to produce outputs of the highest possible quality within the given energy budget.
We introduce a framework for energy-constrained execution with controlled and graceful quality loss. A simple programming model allows users to express the relative importance of computations for the quality of the end result, as well as minimum quality requirements. The significance-aware runtime system uses an application-specific analytical energy model to identify the degree of concurrency and approximation that maximizes quality while meeting user-specified energy constraints. Evaluation on a dual-socket 8-core server shows that the proposed
framework predicts the optimal configuration with high accuracy, enabling energy-constrained executions that result in significantly higher quality compared to loop perforation, a compiler approximation technique.

Characterization of x-ray lens for use in probing high energy density states of matter

By using polycapillary lenses to focus laser-produced x-ray sources to high intensities, an improvement in signal-to-noise ratio can be achieved. Here the He-alpha line emission produced by driving a titanium backlighter target is focused by a polycapillary lens and the output characterized. The x-ray spot is measured to have a peak intensity of 4.5 x 10(7) photons, with a total photon count of 8.8 x 10(8) in 0.13 +/- 0.01 mm(2). This setup is equivalent to placing the backlighter target 3 mm from the sample with a 600 mu m diameter pinhole. The polycapillary lens enables the placement of the backlighter target at a much larger distance from the sample to be studied and therefore has the ability to greatly improve the signal-to-noise ratio on detectors. We demonstrate this with two simple diffraction experiments using pyrolytic graphite and polycrystalline aluminium.

Exploiting Significance of Computations for Energy-Constrained Approximate Computing

Approximate execution is a viable technique for environments with energy constraints, provided that applications are given the mechanisms to produce outputs of the highest possible quality within the available energy budget. This paper introduces a framework for energy-constrained execution with controlled and graceful quality loss. A simple programming model allows developers to structure the computation in different tasks, and to express the relative importance of these tasks for the quality of the end result. For non-significant tasks, the developer can also supply less costly, approximate versions. The target energy consumption for a given execution is specified when the application is launched. A significance-aware runtime system employs an application-specific analytical energy model to decide how many cores to use for the execution, the operating frequency for these cores, as well as the degree of task approximation, so as to maximize the quality of the output while meeting the user-specified energy constraints. Evaluation on a dual-socket 16-core Intel platform using 9 benchmark kernels shows that the proposed framework picks the optimal configuration with high accuracy. Also, a comparison with loop perforation (a well-known compile-time approximation technique), shows that the proposed framework results in significantly higher quality for the same energy budget.

Numerical Analysis on a Dual-Loop Waste Heat Recovery System Coupled with an ORC for Vehicle Applications

The internal combustion (IC) engines exploits only about 30% of the chemical energy ejected through combustion, whereas the remaining part is rejected by means of cooling system and exhausted gas. Nowadays, a major global concern is finding sustainable solutions for better fuel economy which in turn results in a decrease of carbon dioxide (CO2) emissions. The Waste Heat Recovery (WHR) is one of the most promising techniques to increase the overall efficiency of a vehicle system, allowing the recovery of the heat rejected by the exhaust and cooling systems. In this context, Organic Rankine Cycles (ORCs) are widely recognized as a potential technology to exploit the heat rejected by engines to produce electricity. The aim of the present paper is to investigate a WHR system, designed to collect both coolant and exhausted gas heats, coupled with an ORC cycle for vehicle applications. In particular, a coolant heat exchanger (CLT) allows the heat exchange between the water coolant and the ORC working fluid, whereas the exhausted gas heat is recovered by using a secondary circuit with diathermic oil. By using an in-house numerical model, a wide range of working conditions and ORC design parameters are investigated. In particular, the analyses are focused on the regenerator location inside the ORC circuits. Five organic fluids, working in both subcritical and supercritical conditions, have been selected in order to detect the most suitable configuration in terms of energy and exergy efficiencies.

RF energy harvesting two-way cognitive DF relaying with transceiver impairments

This paper analyzes the impact of transceiver impairments on outage probability (OP) and throughput of decode-and-forward two-way cognitive relay (TWCR) networks, where the relay is self-powered by harvesting energy from the transmitted signals. We consider two bidirectional relaying protocols namely, multiple access broadcast (MABC) protocol and time division broadcast (TDBC) protocol, as well as, two power transfer policies namely, dual-source (DS) energy transfer and single-fixed-source (SFS) energy transfer. Closed-form expressions for OP and throughput of the network are derived in the context of delay-limited transmission. Numerical results corroborate our analysis, thereby we can quantify the degradation of OP and throughput of TWCR networks due to transceiver hardware impairments. Under the specific parameters, our results indicate that the MABC protocol achieves asymptotically a higher throughput by 0.65 [bits/s/Hz] than the TDBC protocol, while the DS energy transfer scheme offers better performance than the SFS policy for both relaying protocols.