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Artykuły w czasopismach na temat „Heterogeneous acceleration”

Autor: Grafiati

Data publikacji: 3 czerwca 2025

Data aktualizacji: 31 lipca 2025

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1

Liu, Xing, Ziheng Dai, Qi Wang, and Zhanpeng Li. "Computing Acceleration of Medical Image Processing Based on Multi-Accelerator Heterogeneous Systems." ACM SIGAPP Applied Computing Review 25, no. 1 (2025): 16–24. https://doi.org/10.1145/3727257.3727259.

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Medical image processing (MIP) can make the medical diagnosis more accurate and efficient. However, the operating process of MIP involves many computationally-intensive tasks, which results in a long computational time for MIP. To optimize the processing time of MIP, many research works use the heterogeneous computing architecture (HCA) to accelerate MIP. These works are effective. However, most of them focus on single-accelerator HCA (SA-HCA), which commonly consists of one CPU plus one kind of accelerators, but pay less attention to the multi-accelerator HCA (MA-HCA) such as CPU/FPGA/NPU or

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Chun F. Ong and M. N. Marsono. "Heterogeneous Hardware Architecture with Linear Algebra Acceleration." ELEKTRIKA- Journal of Electrical Engineering 24, no. 1 (2025): 53–56. https://doi.org/10.11113/elektrika.v24n1.633.

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Linear algebra is essential in machine learning for dealing with large datasets. Linear algebra acceleration is directly related to the hardware used. Many works have proposed linear algebra accelerator architectures with the goal of improving energy efficiency and speed. The characterization of trade-offs in balancing acceleration and programmability of software routines is still insufficiently explored, particularly for edge analytics. Therefore, this paper proposes a heterogeneous hardware architecture consisting of a RISC-V system-on-chip and a linear algebra accelerator. Tested on Efinix

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Wei, Xian Min. "Acceleration Components in Heterogeneous Supercomputers." Advanced Materials Research 204-210 (February 2011): 765–68. http://dx.doi.org/10.4028/www.scientific.net/amr.204-210.765.

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General-purpose processors continue to improve computing performance, but its energy consumption has far exceeded the increase in the proportion of performance. Specifically designed for the special purpose processor in the case of relatively low power consumption, can provide better performance. The general-purpose processor as the main control unit, special purpose processors as accelerators consisting of heterogeneous supercomputers will become a trend in supercomputer development. This paper introduces and analyzes several heterogeneous supercomputers used to build the acceleration compone

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4

Rodriguez-Borbon, Jose M., Xiaoyin Ma, Amit K. Roy-Chowdhury, and Walid A. Najjar. "Heterogeneous Acceleration of HAR Applications." IEEE Transactions on Circuits and Systems for Video Technology 30, no. 3 (2020): 888–902. http://dx.doi.org/10.1109/tcsvt.2019.2895304.

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Gou, Xiaopeng, Qi Ge, Quan Guo, et al. "Hardware-Accelerated Data Readout Platform Using Heterogeneous Computing for DNA Data Storage." Applied Sciences 15, no. 9 (2025): 5050. https://doi.org/10.3390/app15095050.

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DNA data storage has emerged as a promising alternative to traditional storage media due to its high density and durability. However, large-scale DNA storage systems generate massive sequencing reads, posing substantial computational complexity and latency challenges for data readout. Here, we propose a novel heterogeneous computing architecture based on a field-programmable gate array (FPGA) to accelerate DNA data readout. The software component, running on a general computing platform, manages data distribution and schedules acceleration kernels. Meanwhile, the hardware acceleration kernel i

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LIU, SHAOSHAN, WON W. RO, CHEN LIU, et al. "INTRODUCING THE EXTREMELY HETEROGENEOUS ARCHITECTURE." Journal of Interconnection Networks 13, no. 03n04 (2012): 1250010. http://dx.doi.org/10.1142/s0219265912500107.

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The computer industry is moving towards two extremes: extremely high-performance high-throughput cloud computing, and low-power mobile computing. Cloud computing, while providing high performance, is very costly. Google and Microsoft Bing spend billions of dollars each year to maintain their server farms, mainly due to the high power bills. On the other hand, mobile computing is under a very tight energy budget, but yet the end users demand ever increasing performance on these devices. This trend indicates that conventional architectures are not able to deliver high-performance and low power c

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Riebler, Heinrich, Gavin Vaz, Tobias Kenter, and Christian Plessl. "Automated code acceleration targeting heterogeneous openCL devices." ACM SIGPLAN Notices 53, no. 1 (2018): 417–18. http://dx.doi.org/10.1145/3200691.3178534.

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Cao, Kai, Qizhong Wu, Lingling Wang, et al. "GPU-HADVPPM4HIP V1.0: using the heterogeneous-compute interface for portability (HIP) to speed up the piecewise parabolic method in the CAMx (v6.10) air quality model on China's domestic GPU-like accelerator." Geoscientific Model Development 17, no. 17 (2024): 6887–901. http://dx.doi.org/10.5194/gmd-17-6887-2024.

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Abstract. Graphics processing units (GPUs) are becoming a compelling acceleration strategy for geoscience numerical models due to their powerful computing performance. In this study, AMD's heterogeneous-compute interface for portability (HIP) was implemented to port the GPU acceleration version of the piecewise parabolic method (PPM) solver (GPU-HADVPPM) from NVIDIA GPUs to China's domestic GPU-like accelerators like GPU-HADVPPM4HIP. Further, it introduced the multi-level hybrid parallelism scheme to improve the total computational performance of the HIP version of the CAMx (Comprehensive Air

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9

Meng, Yuan, and Jun Yang. "Research on heterogeneous acceleration platform based on FPGA." ITM Web of Conferences 45 (2022): 01029. http://dx.doi.org/10.1051/itmconf/20224501029.

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In the context of today’s artificial intelligence, the volume of data is exploding. Although scaling distributed clusters horizontally to cope with the increasing demands on computing power for massive data processing is feasible. But the unlimited addition of nodes will lead to bloated cluster size. Most of the transistors in CPUs are used to build cache memory and control units, which are not efficient for computing operations of massive data processing. Currently, academia uses hardware devices such as GPU (Graphics Processing Unit), ASIC (Application Specific Integrated Circuit), FPGA (Fie

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10

Cornelis, Jan G., Jan Lemeire, Tim Bruylants, and Peter Schelkens. "Heterogeneous acceleration of volumetric JPEG 2000 using OpenCL." International Journal of High Performance Computing Applications 31, no. 3 (2016): 229–45. http://dx.doi.org/10.1177/1094342016646438.

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11

Vranjković, Vuk S., Rastislav J. R. Struharik, and Ladislav A. Novak. "Hardware acceleration of homogeneous and heterogeneous ensemble classifiers." Microprocessors and Microsystems 39, no. 8 (2015): 782–95. http://dx.doi.org/10.1016/j.micpro.2015.10.005.

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Chen, Changchang, Chenchao Bi, Guodong Ji, Hong Wang, Yunru Huo, and Puwei Yu. "Research on Vibration Reduction, Energy Enhancement, and Speed Increase Methods for Drilling String in Deep Heterogeneous Strata." Processes 12, no. 12 (2024): 2645. http://dx.doi.org/10.3390/pr12122645.

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There are a series of problems in the drilling process of deep heterogeneous formations, such as severe drilling string vibration, slow rock-breaking drilling speed, and the short practical working life of drill bits. It is urgent to develop supporting technical methods for breakthroughs. Based on the main characteristics of the drilling environment in deep formations and the results of drilling string dynamics research in recent years, a technical equipment design concept was proposed to use the vibration of the drill string during the drilling process in heterogeneous formations to improve t

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13

Chekunaev, Nikolay I., and Anatoly M. Kaplan. "Acceleration, Retardation and Crack Arrest in Stressed Heterogeneous Structures." Key Engineering Materials 462-463 (January 2011): 506–11. http://dx.doi.org/10.4028/www.scientific.net/kem.462-463.506.

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Hamiltonian of the solid body with a crack inside in field of tensile stresses was derived. Hamiltonian equations describe process of crack propagation. A crack propagation was considered in heterogeneous material when in ground matrix present inclusions with work-of-fracture per unit surface significantly greater than in the matrix. Condition of cracks arrest in such system was found and length of path, passed until crack’s stop, was calculated.

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14

Miyajima, Takaaki, David Thomas, and Hideharu Amano. "Courier: A Toolchain for Application Acceleration on Heterogeneous Platforms." IPSJ Transactions on System LSI Design Methodology 8 (2015): 105–15. http://dx.doi.org/10.2197/ipsjtsldm.8.105.

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15

TOUKONIITTY, E., and D. MURZIN. "Origin of ligand acceleration in heterogeneous ethyl pyruvate hydrogenation." Journal of Catalysis 241, no. 1 (2006): 96–102. http://dx.doi.org/10.1016/j.jcat.2006.04.017.

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Riebler, Heinrich, Gavin Vaz, Tobias Kenter, and Christian Plessl. "Transparent Acceleration for Heterogeneous Platforms With Compilation to OpenCL." ACM Transactions on Architecture and Code Optimization 16, no. 2 (2019): 1–26. http://dx.doi.org/10.1145/3319423.

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González-Domínguez, Jorge, Roberto R. Expósito, and Verónica Bolón-Canedo. "CUDA-JMI: Acceleration of feature selection on heterogeneous systems." Future Generation Computer Systems 102 (January 2020): 426–36. http://dx.doi.org/10.1016/j.future.2019.08.031.

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18

Yuan, Jun, Qiang Zhao, Wei Wang, Xiangsheng Meng, Jun Li, and Qin Li. "Audio Denoising Coprocessor Based on RISC-V Custom Instruction Set Extension." WSEAS TRANSACTIONS ON COMMUNICATIONS 21 (June 25, 2022): 189–95. http://dx.doi.org/10.37394/23204.2022.21.23.

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As a typical active noise control algorithm, FxLMS is widely used in the field of audio denoising. In this paper, an audio denoising coprocessor based on RISC-V custom instruction set extension was designed, and the idea of software and hardware co-design was adopted; based on the traditional pure-hardware implementation, the accelerator optimization design was carried out, and the accelerator was connected to RISC- V core in the form of coprocessor. Meanwhile, the corresponding custom instructions were designed, the compiling environment was established, and the library function of coprocesso

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19

Liang, Yong, Junwen Tan, Zhisong Xie, Zetao Chen, Daoqian Lin, and Zhenhao Yang. "Research on Convolutional Neural Network Inference Acceleration and Performance Optimization for Edge Intelligence." Sensors 24, no. 1 (2023): 240. http://dx.doi.org/10.3390/s24010240.

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In recent years, edge intelligence (EI) has emerged, combining edge computing with AI, and specifically deep learning, to run AI algorithms directly on edge devices. In practical applications, EI faces challenges related to computational power, power consumption, size, and cost, with the primary challenge being the trade-off between computational power and power consumption. This has rendered traditional computing platforms unsustainable, making heterogeneous parallel computing platforms a crucial pathway for implementing EI. In our research, we leveraged the Xilinx Zynq 7000 heterogeneous com

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20

Pérez, Ignacio, and Miguel Figueroa. "A Heterogeneous Hardware Accelerator for Image Classification in Embedded Systems." Sensors 21, no. 8 (2021): 2637. http://dx.doi.org/10.3390/s21082637.

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Convolutional neural networks (CNN) have been extensively employed for image classification due to their high accuracy. However, inference is a computationally-intensive process that often requires hardware acceleration to operate in real time. For mobile devices, the power consumption of graphics processors (GPUs) is frequently prohibitive, and field-programmable gate arrays (FPGA) become a solution to perform inference at high speed. Although previous works have implemented CNN inference on FPGAs, their high utilization of on-chip memory and arithmetic resources complicate their application

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21

Gorchakov, A. V., and L. A. Demidova. "An Approach to Generating Recommendations for Improving the Performance of Software for Heterogeneous Computing Platforms." International Journal of Open Information Technologies 12, no. 4 (2024): 68–76. http://dx.doi.org/10.25559/injoit.2307-8162.12.202404.68-76.

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The widespread use of heterogeneous computing platforms, as well as the incorporation of computationally expensive implementations of intelligent data analysis algorithms into modern software systems leads to the demand in moving software fragments to most suitable hardware accelerators that are available on a heterogeneous computing platform. In this research, we propose an approach to the generation of recommendations for improving the performance of software systems by finding candidate algorithm implementations for hardware acceleration, and by suggesting the most suitable hardware acceler

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22

Liu, Xinyu, Jin Li, Junbang Jiang, and Tiehong Li. "Design of voice command recognition chip based on heterogeneous acceleration." Journal of Physics: Conference Series 2858, no. 1 (2024): 012017. http://dx.doi.org/10.1088/1742-6596/2858/1/012017.

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Abstract Speech, as one of the earliest forms of communication used by humans, can effectively convey information. However, the current deep neural network models for speech recognition are generally large in scale and can only be deployed in the cloud, which imposes high deployment environment requirements and power consumption, thereby limiting their implementation on embedded devices. In the context of end-to-end speech recognition, a series of challenges are encountered, including power consumption constraints, computing power limitations, network dependencies, privacy protection, bandwidt

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23

Kulkarni, Amey, Colin Shea, Tahmid Abtahi, Houman Homayoun, and Tinoosh Mohsenin. "Low Overhead CS-Based Heterogeneous Framework for Big Data Acceleration." ACM Transactions on Embedded Computing Systems 17, no. 1 (2018): 1–25. http://dx.doi.org/10.1145/3092944.

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Ferreirinha, Tomás, Rúben Nunes, Leonardo Azevedo, et al. "Acceleration of stochastic seismic inversion in OpenCL-based heterogeneous platforms." Computers & Geosciences 78 (May 2015): 26–36. http://dx.doi.org/10.1016/j.cageo.2015.02.005.

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Kharlamov, V. F., and F. V. Kharlamov. "Role of adsorption complexes in catalytic acceleration of heterogeneous reactions." Journal of Surface Investigation. X-ray, Synchrotron and Neutron Techniques 3, no. 4 (2009): 651–57. http://dx.doi.org/10.1134/s1027451009040284.

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Páll, Szilárd, Artem Zhmurov, Paul Bauer, et al. "Heterogeneous parallelization and acceleration of molecular dynamics simulations in GROMACS." Journal of Chemical Physics 153, no. 13 (2020): 134110. http://dx.doi.org/10.1063/5.0018516.

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Wang, Andrew, Carlota Bozal-Ginesta, Sai Govind Hari Kumar, Alán Aspuru-Guzik, and Geoffrey A. Ozin. "Designing materials acceleration platforms for heterogeneous CO2 photo(thermal)catalysis." Matter 6, no. 5 (2023): 1334–47. http://dx.doi.org/10.1016/j.matt.2023.03.015.

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Xekalaki, Maria, Juan Fumero, Athanasios Stratikopoulos, et al. "Enabling Transparent Acceleration of Big Data Frameworks Using Heterogeneous Hardware." Proceedings of the VLDB Endowment 15, no. 13 (2022): 3869–82. http://dx.doi.org/10.14778/3565838.3565842.

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The ever-increasing demand for high performance Big Data analytics and data processing, has paved the way for heterogeneous hardware accelerators, such as Graphics Processing Units (GPUs) and Field Programmable Gate Arrays (FPGAs), to be integrated into modern Big Data platforms. Currently, this integration comes at the cost of programmability since the end-user Application Programming Interface (APIs) must be altered to access the underlying heterogeneous hardware. For example, current Big Data frameworks, such as Apache Spark, provide a new API that combines the existing Spark programming mo

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Liu, Chi-Chun, and Stephen G. Ryan. "Income Smoothing over the Business Cycle: Changes in Banks' Coordinated Management of Provisions for Loan Losses and Loan Charge-Offs from the Pre-1990 Bust to the 1990s Boom." Accounting Review 81, no. 2 (2006): 421–41. http://dx.doi.org/10.2308/accr.2006.81.2.421.

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Prior research shows that during the pre-1990 bust financially weak banks managed income upward by delaying provisions for losses on heterogeneous loans. In contrast, we predict and find that during the 1990s boom profitable banks managed income downward by accelerating provisions for losses on homogeneous loans. Profitable banks obscured their income smoothing by accelerating charge-offs of homogeneous loans and by recording more gross charge-offs to offset recoveries of previously charged-off loans. Over the three years subsequent to the acceleration of charge-offs, they had higher and more

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Yuan, Jun, Qiang Zhao, Wei Wang, Xiangsheng Meng, Jun Li, and Qin Li. "Audio Denoising Coprocessor Based on RISC-V Custom Instruction Set Extension." Acoustics 4, no. 3 (2022): 538–53. http://dx.doi.org/10.3390/acoustics4030033.

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As a typical active noise control algorithm, Filtered-x Least Mean Square (FxLMS) is widely used in the field of audio denoising. In this study, an audio denoising coprocessor based on Retrenched Injunction System Computer-V (RISC-V), a custom instruction set extension was designed and a software and hardware co-design was adopted; based on the traditional pure hardware implementation, the accelerator optimization design was carried out, and the accelerator was connected to the RISC-V core in the form of coprocessor. Meanwhile, the corresponding custom instructions were designed, the compiling

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Garcia-Hernandez, Jose Juan, Miguel Morales-Sandoval, and Erick Elizondo-Rodríguez. "A Flexible and General-Purpose Platform for Heterogeneous Computing." Computation 11, no. 5 (2023): 97. http://dx.doi.org/10.3390/computation11050097.

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In the big data era, processing large amounts of data imposes several challenges, mainly in terms of performance. Complex operations in data science, such as deep learning, large-scale simulations, and visualization applications, can consume a significant amount of computing time. Heterogeneous computing is an attractive alternative for algorithm acceleration, using not one but several different kinds of computing devices (CPUs, GPUs, or FPGAs) simultaneously. Accelerating an algorithm for a specific device under a specific framework, i.e., CUDA/GPU, provides a solution with the highest possib

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Cheela, Bhagath, André DeHon, Jesús Fernández-Villaverde, and Alessandro Peri. "Programming FPGAs for economics: An introduction to electrical engineering economics." Quantitative Economics 16, no. 1 (2025): 49–87. https://doi.org/10.3982/qe2344.

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We show how to use field‐programmable gate arrays (FPGAs) and their associated high‐level synthesis ( HLS) compilers to solve heterogeneous agent models with incomplete markets and aggregate uncertainty (Krusell and Smith (1998)). We document that the acceleration delivered by one single FPGA is comparable to that provided by using 69 CPU cores in a conventional cluster. The time to solve 1200 versions of the model drops from 8 hours to 7 minutes, illustrating a great potential for structural estimation. We describe how to achieve multiple acceleration opportunities—pipeline, data‐level parall

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Cano, Rafael, Alexander F. Schmidt, and Gerard P. McGlacken. "Direct arylation and heterogeneous catalysis; ever the twain shall meet." Chemical Science 6, no. 10 (2015): 5338–46. http://dx.doi.org/10.1039/c5sc01534k.

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We bring together the mature, yet poorly-understood, subject of heterogeneous catalysis with the rapidly expanding area of Direct Arylation, with a view towards the acceleration of catalyst design and the understanding of catalyst behaviour.

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KUCHERENKO, Yu A., A. P. PYLAEV, V. D. MURZAKOV, A. V. BELOMESTNIH, V. N. POPOV, and A. A. TYAKTEV. "Experimental study into the Rayleigh–Taylor turbulent mixing zone heterogeneous structure." Laser and Particle Beams 21, no. 3 (2003): 375–79. http://dx.doi.org/10.1017/s0263034603213136.

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Experiments conducted on the SOM facility at the Russian Federal Nuclear Center–VNIITF, concerning the turbulent mixing induced by the Rayleigh–Taylor instability in a three-layer system of immiscible liquids are described. The fluids are contained in a small tank 6.4 cm × 5.4 cm × 12 cm, which is accelerated vertically downward by a gas gun. The mixing layer evolution was imaged by seeding one of the fluids with particles and using a bidirectional light sheet method (refractive index matching was used to minimize measurement errors). Experiments were performed for two different accelerations

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Papadogiannaki, Eva, and Sotiris Ioannidis. "Acceleration of Intrusion Detection in Encrypted Network Traffic Using Heterogeneous Hardware." Sensors 21, no. 4 (2021): 1140. http://dx.doi.org/10.3390/s21041140.

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More than 75% of Internet traffic is now encrypted, and this percentage is constantly increasing. The majority of communications are secured using common encryption protocols such as SSL/TLS and IPsec to ensure security and protect the privacy of Internet users. However, encryption can be exploited to hide malicious activities, camouflaged into normal network traffic. Traditionally, network traffic inspection is based on techniques like deep packet inspection (DPI). Common applications for DPI include but are not limited to firewalls, intrusion detection and prevention systems, L7 filtering, a

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Yan, Shun, Qiang Liu, Jiajun Li, and Liang Han. "Heterogeneous Acceleration of Hybrid PSO-QN Algorithm for Neural Network Training." IEEE Access 7 (2019): 161499–509. http://dx.doi.org/10.1109/access.2019.2951710.

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Wachowiak, Mark P., Mitchell C. Timson, and David J. DuVal. "Adaptive Particle Swarm Optimization with Heterogeneous Multicore Parallelism and GPU Acceleration." IEEE Transactions on Parallel and Distributed Systems 28, no. 10 (2017): 2784–93. http://dx.doi.org/10.1109/tpds.2017.2687461.

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Molina, Romina, Julio Dondo Gazzano, Fernando Rincon, et al. "Heterogeneous SoC-based acceleration of MPEG-7 compliance image retrieval process." Journal of Real-Time Image Processing 15, no. 1 (2018): 161–72. http://dx.doi.org/10.1007/s11554-018-0788-6.

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宋, 奇伟. "Optimization and Acceleration Algorithm for Heterogeneous Platforms Based on ARM + DSP." Modeling and Simulation 12, no. 03 (2023): 2318–29. http://dx.doi.org/10.12677/mos.2023.123213.

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Xiong, Hao, Kelin Sun, Bing Zhang, Jingchuan Yang, and Huiping Xu. "Deep-Sea: A Reconfigurable Accelerator for Classic CNN." Wireless Communications and Mobile Computing 2022 (February 2, 2022): 1–23. http://dx.doi.org/10.1155/2022/4726652.

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To meet the changing real-time edge engineering application requirements of CNN, aiming at the lack of universality and flexibility of CNN hardware acceleration architecture based on ARM+FPGA, a general low-power all pipelined CNN hardware acceleration architecture is proposed to cope with the continuously updated CNN algorithm and accelerate in hardware platforms with different resource constraints. In the framework of the general hardware architecture, a basic instruction set belonging to the architecture is proposed, which can be used to calculate and configure different versions of CNN alg

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Liu, Jingyang, Xiangrui Zeng, Guijuan Han, and Bibo Zhu. "SAS Sub-array focusing back-projection imaging method under heterogeneous computing." Journal of Physics: Conference Series 2990, no. 1 (2025): 012023. https://doi.org/10.1088/1742-6596/2990/1/012023.

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Abstract The synthetic aperture sonar (SAS) back projection (BP) algorithm is characterized by its ability to adapt to complex trajectories, facilitate motion error compensation, and achieve precise imaging. However, the computational complexity of the BP algorithm is high, making real-time imaging difficult to achieve in miniaturized and lightweight signal processing units. This paper proposes a focused back-projection imaging method for SAS sub-arrays under heterogeneous computing and leverages the high-performance parallel computing capabilities of the graphics processing unit (GPU) to acce

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Ma, Ke, Lin Han, Jian-dong Shang, Jing-ming Xie, and Hao Zhang. "Optimized realization of Quantum Fourier Transform for domestic DCU accelerator." Journal of Physics: Conference Series 2258, no. 1 (2022): 012065. http://dx.doi.org/10.1088/1742-6596/2258/1/012065.

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Abstract Quantum Fourier Transform (QFT) is a key part of quantum algorithms such as Shor algorithm, Grover algorithm, and quantum phase estimation algorithm. The “Songshan” supercomputer system adopts the heterogeneous architecture of domestic CPU+DCU. The simulation implementation of the quantum Fourier transform on the “Songshan” supercomputer can promote the research and optimization of related quantum algorithms. Based on the HIP heterogeneous programming model, this paper first maps the phase shift transformation R gate operation of the QFT transformation to the DCU accelerator, and init

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Sudakov, Vladimir, and Yuri Titov. "Matrix-Based ACO for Solving Parametric Problems Using Heterogeneous Reconfigurable Computers and SIMD Accelerators." Mathematics 13, no. 8 (2025): 1284. https://doi.org/10.3390/math13081284.

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This paper presents a new matrix representation of ant colony optimization (ACO) for solving parametric problems. This representation allows us to perform calculations using matrix processors and single-instruction multiple-data (SIMD) calculators. To solve the problem of stagnation of the method without a priori information about the system, a new probabilistic formula for choosing the parameter value is proposed, based on the additive convolution of the number of pheromone weights and the number of visits to the vertex. The method can be performed as parallel calculations, which accelerates

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Andreev, A. A., and K. Yu Platonov. "Hybrid model of ion acceleration in laser plasma of flat heterogeneous target." Optics and Spectroscopy 111, no. 2 (2011): 191–99. http://dx.doi.org/10.1134/s0030400x11080030.

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Vaidya, Prakash D., and Rushikesh K. Junghare. "ACCELERATION OF THE WET OXIDATION REACTION OF PIPERAZINE BY HETEROGENEOUS Ru/TiO2CATALYST." Chemical Engineering Communications 198, no. 8 (2011): 992–1003. http://dx.doi.org/10.1080/00986445.2011.545300.

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Li, Peilong, Yan Luo, and Jun Yang. "Transformer: Run-time reprogrammable heterogeneous architecture for transparent acceleration of dynamic workloads." Journal of Parallel and Distributed Computing 86 (December 2015): 45–61. http://dx.doi.org/10.1016/j.jpdc.2015.08.002.

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Samejima, Fumiko. "Acceleration model in the heterogeneous case of the general graded response model." Psychometrika 60, no. 4 (1995): 549–72. http://dx.doi.org/10.1007/bf02294328.

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Asghari-Moghaddam, Hadi, Amin Farmahini-Farahani, Katherine Morrow, Jung Ho Ahn, and Nam Sung Kim. "Near-DRAM Acceleration with Single-ISA Heterogeneous Processing in Standard Memory Modules." IEEE Micro 36, no. 1 (2016): 24–34. http://dx.doi.org/10.1109/mm.2016.8.

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Feng, Yiming, Shihong Hu, Lingqiang Chen, and Guanghui Li. "An intelligent scheduling framework for DNN task acceleration in heterogeneous edge networks." Computer Communications 201 (March 2023): 91–101. http://dx.doi.org/10.1016/j.comcom.2023.01.019.

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Chen, Xi, Kun Zhang, and Wei Wang. "Seismic Stability Analysis of Tunnel Faces in Heterogeneous and Anisotropic Soils Using Modified Pseudodynamic Method." Sustainability 15, no. 14 (2023): 11083. http://dx.doi.org/10.3390/su151411083.

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This work assesses the seismic stability of tunnel faces advanced in heterogeneous and anisotropic soils based on the plastic limit theorem. A discretized kinematic velocity field respecting the normal flow rule is generated via a point-to-point discretization technique. The distribution of soil parameters in the depth direction including cohesion, friction angle, and unit weight are considered by four kinds of profiles. The variation in cohesion with shear direction caused by consolidation and sedimentation is considered by including an anisotropy coefficient. The seismic acceleration is repr

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