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   Articles with "gpus" as a keyword



GPUs in subsurface simulation: an investigation

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recommendations! Published in 2017 at "Engineering with Computers"

DOI: 10.1007/s00366-017-0506-1

Abstract: Subsurface simulations are computationally intensive tasks and require a considerable amount of time to solve. To gain computational speed in simulating subsurface scenarios, this paper investigates the use of graphical processing units (GPUs). Accelerators such… read more here.

Keywords: subsurface simulation; subsurface; simulation investigation; gpus subsurface ... See more keywords
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Exploiting parallel graphics processing units to improve association rule mining in transactional databases using butterfly optimization algorithm

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recommendations! Published in 2021 at "Cluster Computing"

DOI: 10.1007/s10586-021-03369-2

Abstract: Extracting association rules from huge amounts of data is an essential method in data mining that can provide valuable knowledge from datasets for various applications. In addition to a variety of traditional and parallel association… read more here.

Keywords: association rule; association; rule mining; optimization ... See more keywords

A Novel Performance Prediction Model for Mobile GPUs

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recommendations! Published in 2018 at "IEEE Access"

DOI: 10.1109/access.2018.2816040

Abstract: With the fast-growing development of mobile devices, the application of high-end three-dimensional (3-D) graphics is expanding to include usage in mobile platforms. Recent mobile application processors are equipped with a multicore CPU and a mobile… read more here.

Keywords: novel performance; mobile gpus; model; gpus ... See more keywords
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Toward QoS-Awareness and Improved Utilization of Spatial Multitasking GPUs

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recommendations! Published in 2022 at "IEEE Transactions on Computers"

DOI: 10.1109/tc.2021.3064352

Abstract: Datacenters use GPUs to provide the significant computing throughput required by emerging user-facing services. The diurnal user access pattern of user-facing services provides a strong incentive to co-located applications for better GPU utilization, and prior… read more here.

Keywords: user facing; gpus; multitasking gpus; facing services ... See more keywords

Non-Clairvoyant Scheduling of Distributed Machine Learning With Inter-Job and Intra-Job Parallelism on Heterogeneous GPUs

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recommendations! Published in 2024 at "IEEE Transactions on Cloud Computing"

DOI: 10.1109/tcc.2024.3414440

Abstract: Distributed machine learning (DML) has shown great promise in accelerating model training on multiple GPUs. To increase GPU utilization, a common practice is to let multiple learning jobs share GPU clusters, where the most fundamental… read more here.

Keywords: parallelism; inter job; gpus; machine learning ... See more keywords

Building a Lightweight Trusted Execution Environment for Arm GPUs

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recommendations! Published in 2024 at "IEEE Transactions on Dependable and Secure Computing"

DOI: 10.1109/tdsc.2023.3334277

Abstract: A wide range of Arm endpoints leverage integrated and discrete GPUs to accelerate computation. However, Arm GPU security has not been explored by the community. Existing work has used Trusted Execution Environments (TEEs) to address… read more here.

Keywords: gpus; security; arm gpus; trusted execution ... See more keywords
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SMGuard: A Flexible and Fine-Grained Resource Management Framework for GPUs

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recommendations! Published in 2018 at "IEEE Transactions on Parallel and Distributed Systems"

DOI: 10.1109/tpds.2018.2848621

Abstract: GPUs have been becoming an indispensable computing platform in data centers, and co-locating multiple applications on the same GPU is widely used to improve resource utilization. However, performance interference due to uncontrolled resource contention severely… read more here.

Keywords: latency sensitive; resource; fine grained; smguard ... See more keywords

Visibility Rendering Order: Improving Energy Efficiency on Mobile GPUs through Frame Coherence

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recommendations! Published in 2019 at "IEEE Transactions on Parallel and Distributed Systems"

DOI: 10.1109/tpds.2018.2866246

Abstract: During real-time graphics rendering, objects are processed by the GPU in the order they are submitted by the CPU, and occluded surfaces are often processed even though they will end up not being part of… read more here.

Keywords: rendering order; gpus; order; visibility rendering ... See more keywords

Max-Tree Computation on GPUs

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recommendations! Published in 2022 at "IEEE Transactions on Parallel and Distributed Systems"

DOI: 10.1109/tpds.2022.3158488

Abstract: In Mathematical Morphology, the max-tree is a region-based representation that encodes the inclusion relationship of the threshold sets of an image. This tree has proved useful in numerous image processing applications. For the last decade,… read more here.

Keywords: mathematical morphology; max tree; tree computation; gpus ... See more keywords

The Megapixel Approach for Efficient Execution of Irregular Wavefront Algorithms on GPUs

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recommendations! Published in 2025 at "IEEE Transactions on Parallel and Distributed Systems"

DOI: 10.1109/tpds.2025.3612696

Abstract: Morphological operations are critical in high-resolution biomedical image processing. Their efficient execution relies on an irregular flood-filling strategy consolidated in the Irregular Wavefront Propagation Pattern (IWPP). IWPP was designed for GPUs and achieved significant gains… read more here.

Keywords: irregular wavefront; efficient execution; execution; gpus ... See more keywords

Pod Placement Techniques to Avoid Job Failures Due to Low GPU Memory in a Kubernetes Environment with Shared GPUs

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recommendations! Published in 2024 at "International Journal on Advanced Science, Engineering and Information Technology"

DOI: 10.18517/ijaseit.14.5.11589

Abstract: In a container-based cloud environment, GPUs have the advantage of providing high-performance computation to multiple users, and through GPU sharing, many GPU container users can be accommodated over the number of physical GPUs. This increases… read more here.

Keywords: pod placement; environment; memory; gpus ... See more keywords