Faculty Publications
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Publications by NITK Faculty
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Item Accurate Router Level Estimation of Network-on-Chip Architectures using Learning Algorithms(Institute of Electrical and Electronics Engineers Inc., 2019) Kumar, A.; Talawar, B.The problem of intra-communication between the Intellectual Properties(IPs) due to the rise in the amount of cores on single chips in System-on-Chip(SoC). Network-on-Chips(NoCs) has emerged as a reliable on-chip communication framework for Chip Multiprocessors and SoCs. Estimating NoC power and performance in the early stages has become crucial. We employ Machine Learning(ML) approaches to estimate architecture-level on-chip router models and performance. Experiments were carried out with distinct topology sizes with various virtual channels, injection rates, and traffic patterns. Booksim and Orion simulators are used to validate the results. Approximately 6% to 8% prediction error and a minimum speedup of 1500 × to 2000 × were shown in the framework. © 2019 IEEE.Item UPM-NoC: Learning based framework to predict performance parameters of mesh architecture in on-chip networks(Springer, 2020) Kumar, A.; Talawar, B.Conventional Bus-based On-Chips are replaced by Packet-switched Network-on-Chip (NoC) as a large number of cores are contained on a single chip. Cycle accurate NoC simulators are essential tools in the earlier stages of design. Simulators which are cycle accurate performs gradually as the architecture size of NoC increases. NoC architectures need to be validated against discrete synthetic traffic patterns. The overall performance of NoC architecture depends on performance parameters like network latency, packet latency, flit latency, and hop count. Hence we propose a Unified Performance Model (UPM) to deliver precise measurements of NoC performance parameters. This framework is modeled using distinct Machine Learning (ML) regression algorithms to predict performance parameters of NoCs considering different synthetic traffic patterns. The UPM framework can be used to analyze the performance parameters of Mesh NoC architecture. Results obtained were compared against the widely used cycle accurate Booksim simulator. Experiments were conducted by varying topology size from 2×2 to 50×50 with different virtual channels, traffic patterns, and injection rates. The framework showed an approximate prediction error of 5% to 6% and overall minimum speedup of 3000× to 3500×. © Springer Nature Singapore Pte Ltd 2020.Item Performance analysis of radio-over-free-space optical communication system with spatial diversity over combined channel model(Springer, 2022) Kumar, A.; Krishnan, P.Radio over Free Space Optical (RoFSO) communication is accepted as one of the promising technologies in communication systems that can fulfill the demands of high bandwidth and high data rate because it has an inherent quality of transmission capacity significantly more than what is provided by radio transmission technologies. It is a low power, high data rate, unlicensed spectrum, and large bandwidth wireless technology. Nevertheless, the full potential of the RoFSO communication system can be utilized only by overcoming the adverse effects of the atmospheric channel, which are scattering, absorption, and turbulence. Pointing error is also another factor responsible for the deterioration of the performance of the RoFSO system. In this paper, spatial diversity at the transmitting and receiving ends is used to improve the performance of the RoFSO system in various turbulence and weather conditions. The Malaga distribution has been used to model atmospheric turbulence. For single input single output (SISO), single input Multiple output (SIMO), multiple input single output (MISO), multiple input multiple output (MIMO) configurations, closed form expressions for average bit error rate (BER) have been estimated. To improve the performance of the proposed system, the two combining techniques, Optimal Combining and Equal Gain Combining, are being considered. The results obtained are compared to various configurations such as SISO, SIMO, MISO, and MIMO cases. The result shows that MIMO offers better average BER performance compared with SISO, SIMO and MISO cases. The 4 × 4 MIMO case has an average BER of 10 - 9 at an average SNR of 25 dB, but the SISO case has an average BER of 10 - 1 at the same average SNR. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.Item LBF-NoC: Learning-Based Framework to Predict Performance, Power and Area for Network-On-Chip Architectures(World Scientific, 2022) Kumar, A.; Talawar, B.Extensive large-scale data and applications have increasing requests for high-performance computations which is fulfilled by Chip Multiprocessors (CMP) and System-on-Chips (SoCs). Network-on-Chips (NoCs) emerged as the reliable on-chip communication framework for CMPs and SoCs. NoC architectures are evaluated based on design parameters such as latency, area, and power. Cycle-accurate simulators are used to perform the design space exploration of NoC architectures. Cycle-accurate simulators become slow for interactive usage as the NoC topology size increases. To overcome these limitations, we employ a Machine Learning (ML) approach to predict the NoC simulation results within a short span of time. LBF-NoC: Learning-based framework is proposed to predict performance, power and area for Direct and Indirect NoC architectures. This provides chip designers with an efficient way to analyze various NoC features. LBF-NoC is modeled using distinct ML regression algorithms to predict overall performance of NoCs considering different synthetic traffic patterns. The performance metrics of five different (Mesh, Torus, Cmesh, Fat-Tree and Flattened Butterfly) NoC architectures can be analyzed using the proposed LBF-NoC framework. BookSim simulator is employed to validate the results. Various architecture sizes from 2×2 to 45×45 are used in the experiments considering various virtual channels, traffic patterns, and injection rates. The prediction error of LBF-NoC is 6% to 8%, and the overall speedup is 5000× to 5500× with respect to BookSim simulator. © 2022 World Scientific Publishing Company.Item Cerium doping of FeS2 for the effective hydrogen evolution reaction (HER) electrocatalysis(Taylor and Francis Ltd., 2025) Hegde, A.P.; Gonde, A.; Kumawat, A.; Mukesh, P.; Lakshmisagar, G.; Kumar, A.; Nagaraja, H.S.Crafting and developing nanostructured electrocatalyst materials that are both active and stable plays a pivotal role in the shift toward economically viable hydrogen production through electrochemical water splitting, paving the way for the future replacement of fossil fuels. Such materials need to be cost-effective, simple to produce, and durable. In this context, the current research delves into improving the hydrogen evolution reaction (HER) electrocatalytic performance by incorporating cerium (Ce) into iron disulfide (FeS2) catalysts, using an uncomplicated hydrothermal fabrication approach. The study systematically examines the effects of various Ce doping levels on electrocatalytic activity. Notably, the catalyst with 15% Ce doping demonstrated exceptional efficiency, reducing the overpotential to 369 mV at 100 mA cm?2 current density. This enhanced performance can be attributed to the reduction in total charge-transfer resistance and a significant increase in the electrochemical active surface area (ECSA). Furthermore, the durability assessment of the 15% Ce-doped sample revealed its ability to sustain its catalytic activity for over 100 h under a continuous HER operation at 300 mA cm-2, with low performance-falloff. These results highlight the potential of Ce-dopping of FeS2 catalysts as a formidable choice for achieving efficient and long lasting HER electrocatalysis. © 2025 Taylor & Francis Group, LLC.Item Insights into the potential of Sb alloyed Cu2AgBiI6-based solar cells: For efficient indoor energy-harvesting(Elsevier Ltd, 2025) Kumar, A.; Siddharth, G.; Dwivedi, P.; Pandey, S.K.; Sengar, B.S.; Garg, V.Recently, indoor photovoltaics have attracted significant attention due to their remarkable capability to generate power from indoor light sources. This work investigates the performance of perovskite-inspired material Sb alloyed Cu2AgBiI6 (CABI-Sb) based indoor photovoltaic device, which has shown a power conversion efficiency of 9.53 %, reported in a recent experimental study by B. Al-Anesi et al. The baseline model of the CABI-Sb device structure (FTO/TiO2/CABI-Sb/Spiro-OMeTAD/Au) is developed in SCAPS-1D using the earlier reported experimental data. Baseline model parameters under WLED illumination are Jsc: 128.2 µA/cm2, Voc: 0.51 V, FF: 66.57 %, and PCE: 9.53 %, with a minor deviation of less than 1 %, which validates the developed model with experimental data. The performance of the device is fine-tuned by optimizing 1) Absorber thickness and defect density 2) Electron Transport Layer (ETL) doping density, conduction band offset (CBO) and interface defect density between the ETL/absorber (TiO2 /CABI-Sb) interface, 3) Hole Transport Layer (HTL) doping density, valence band offset (VBO) and interface defect density between HTL/absorber (CABI-Sb/Spiro-OMeTAD) interface, 4) work function of contacts, and 5) Series and shunt resistance were optimized. The performance parameters of the optimized device under the WLED illumination are Jsc: 1.84 mA/cm2, Voc: 1.60 V, FF: 86.78 %, and PCE: 49.31 %. A remarkable improvement in PCE is achieved from 9.53 % to 49.31 %. Further, to validate the suitability of the optimized device under different indoor environments, optimized device performance is evaluated under different lux intensities of WLED (6500 K), WLED (2700 K), compact fluorescent light (CFL), and halogen. © 2024 International Solar Energy Society