NeuroBench: Advancing Neuromorphic Computing through Collaborative, Fair and Representative Benchmarking

The field of neuromorphic computing holds great promise in terms of advancing computing efficiency and capabilities by following brain-inspired principles. However, the rich diversity of techniques employed in neuromorphic research has resulted in a lack of clear standards for benchmarking, hindering effective evaluation of the advantages and strengths of neuromorphic methods compared to traditional deep-learning-based methods. This paper presents a collaborative effort, bringing together members from academia and the industry, to define benchmarks for neuromorphic computing: NeuroBench. The goals of NeuroBench are to be a collaborative, fair, and representative benchmark suite developed by the community, for the community. In this paper, we discuss the challenges associated with benchmarking neuromorphic solutions, and outline the key features of NeuroBench. We believe that NeuroBench will be a significant step towards defining standards that can unify the goals of neuromorphic computing and drive its technological progress. Please visit neurobench.ai for the latest updates on the benchmark tasks and metrics

NeuroBench:Advancing Neuromorphic Computing through Collaborative, Fair and Representative Benchmarking

The field of neuromorphic computing holds great promise in terms of advancing computing efficiency and capabilities by following brain-inspired principles. However, the rich diversity of techniques employed in neuromorphic research has resulted in a lack of clear standards for benchmarking, hindering effective evaluation of the advantages and strengths of neuromorphic methods compared to traditional deep-learning-based methods. This paper presents a collaborative effort, bringing together members from academia and the industry, to define benchmarks for neuromorphic computing: NeuroBench. The goals of NeuroBench are to be a collaborative, fair, and representative benchmark suite developed by the community, for the community. In this paper, we discuss the challenges associated with benchmarking neuromorphic solutions, and outline the key features of NeuroBench. We believe that NeuroBench will be a significant step towards defining standards that can unify the goals of neuromorphic computing and drive its technological progress. Please visit neurobench.ai for the latest updates on the benchmark tasks and metrics

NeuroBench:A Framework for Benchmarking Neuromorphic Computing Algorithms and Systems

Neuromorphic computing shows promise for advancing computing efficiency and capabilities of AI applications using brain-inspired principles. However, the neuromorphic research field currently lacks standardized benchmarks, making it difficult to accurately measure technological advancements, compare performance with conventional methods, and identify promising future research directions. Prior neuromorphic computing benchmark efforts have not seen widespread adoption due to a lack of inclusive, actionable, and iterative benchmark design and guidelines. To address these shortcomings, we present NeuroBench: a benchmark framework for neuromorphic computing algorithms and systems. NeuroBench is a collaboratively-designed effort from an open community of nearly 100 co-authors across over 50 institutions in industry and academia, aiming to provide a representative structure for standardizing the evaluation of neuromorphic approaches. The NeuroBench framework introduces a common set of tools and systematic methodology for inclusive benchmark measurement, delivering an objective reference framework for quantifying neuromorphic approaches in both hardware-independent (algorithm track) and hardware-dependent (system track) settings. In this article, we present initial performance baselines across various model architectures on the algorithm track and outline the system track benchmark tasks and guidelines. NeuroBench is intended to continually expand its benchmarks and features to foster and track the progress made by the research community

Enhanced seed germination and plant growth by atmospheric pressure cold air plasma: combined effect of seed and water treatment

International audienceThe combined effect of non-thermal plasma treatment of water and seeds on the rate of germination and plants growth of radish (Raphanus sativus), tomato (Solanum lycopersicum), and sweet pepper (Capsicum annum) have been investigated using dielectric barrier discharges in air under atmospheric pressure and room temperature. A cylindrical double dielectric barrier discharge reactor is used for water activation and a plate-to-plate double DBD reactor is employed for seed treatment. The activation of water, for 15 and 30 min, lead to acidic solutions (pH  3) with moderate concentrations of nitrate (NO3-) and hydrogen peroxide (H2O2). Plasma activated water (PAW) has shown a significant impact on germination as well as plant growth for the three types of seeds used. Interestingly, the positive effect, in seed germination and seedling growth, has been observed when the PAW and plasma-treated seeds (10 and 20 min) were combined. In one hand, when the seeds were (tomato and pepper) exposed to 10 min plasma and watered with PAW-15 for first 9 days followed by tap water for 51 days, the stem length is increased about 60% as compared to control sample. On the second hand, for longer exposures of seeds and water to plasma discharges, a negative effect is observed. For instance, plasma-treated seeds watered with PAW-30, the plant growth and vitality were decreased as compared to control sample. These results revealed that the developed cold plasma reactors could be used to significantly improve the seed germination as well as plant growth, nevertheless, the plasma treatment time has to be optimized for each seeds

Characterization of afterglow kinetics at atmospheric pressures by emission spectroscopy: II. Reactions of neon ions with Xe

International audienceThe afterglow of a 1 kA, 10 ns duration discharge in neon at 1.1-4.0 bar pressure containing up to 30 mbar of reactant admixture Xe was studied by time-resolved emission spectroscopy. Destruction frequencies of neon ions have been determined experimentally both from the selectively excited fluorescence of N2+ and from the radiation of excited xenon atoms. These data confirm the existence of a termolecular charge-transfer reaction of Ne2+ with Xe, the corresponding rate coefficient being (2.6+-0.3)10-30 cm6s-1. Also the fact that vibrationally excited Ne2+ ions play an important role was confirmed. A persistent source of ionization at late afterglow times has been studied in some detail and was interpreted in terms of collisions between xenon atoms in their first excited states 3P2 and 3P1. The decay processes of these atoms were identified as partially trapped resonance radiation and three-body conversion to Xe2 dimer

EXPERIMENTAL UNDERSTANDING OF OZONE DECOMPOSITION INSIDE A LOW TEMPERATURE COMBUSTION ENGINE

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Monitoring hydrodynamic effects in helium atmospheric pressure plasma jet by resonance broadening emission line

International audienceAtmospheric pressure plasma jet (APPJ) producing guided ionization wave (IW) in helium (He) is investigated by optical emission spectroscopy (OES) with regard to the hydrodynamics, i.e. helium-air mixing and the buoyancy force. A non-invasive method based on the analysis of the resonant broadening line profile is introduced to diagnose the action of the IW on the He laminar flow. The total force acting upon the gas flow (summarizing the electohydrodynamic (EHD) force and the buoyancy force (fb) is investigated experimentally. Quantitative results are in agreement with published data obtained by numerical modeling. Furthermore, low content of air fraction diffusing into the He flow can be determined from the resonant broadening line profile. The latter is of high interest in biomedical and agriculture applications as well as material surface and liquid activation

Energy deposition effect on the NOx remediation in oxidative media using atmospheric non thermal plasmas

Dielectric barrier discharges (DBDs) have been investigated under a wide range of experimental conditions (pulsed and sinusoidal excitation, input energy, frequency, and residence time) to remediate NOx from atmospheric O2 rich gas streams. In a given reactor under identical gas composition and equivalent energy density deposition, results show that the main parameter which controls the efficiency of the plasma process is the energy deposition mode. For example, in a pulsed DBD processing at energy density deposition of 30 J/L, 25% of NOx and 40% of C3H6 were converted at 35 mJ/pulse whereas, at 195 mJ/pulse these values were 0% and 15%, respectively. Furthermore, significantly different end products were observed when changing the nature of electrical excitation

Experimental Understanding of Ozone Decomposition inside a Low-Temperature Combustion Engine

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Experimental assessment of ozone production by multichannel plasma discharges for automotive applications

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