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Speeding up a Video Summarization Approach Using GPUs and Multicore CPUs
2014
Procedia Computer Science
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This paper introduces parallelizations of a summarization method called VSUMM, targetting either Graphic Processor Units (GPUs) or multicore Central Processor Units (CPUs), and ultimately a sensible distribution ...
We performed experiments using 180 videos varying frame resolution (320 × 240, 640 × 360, and 1920 × 1080) and video length (1, 3, 5, 10, 20, and 30 minutes). ...
Speeding up a Video Summarization Approach Almeida et al. ...
doi:10.1016/j.procs.2014.05.015
fatcat:rsjtwkwtvrf3zo6wzvlpk6ztja
Deep Tensor Convolution on Multicores
[article]
2017
arXiv
pre-print
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These networks have improved performance of video and volumetric image analysis, but have been limited in size due to the low memory ceiling of GPU hardware. ...
Treating 2-dimensional ConvNets as a special (and the least beneficial) case of our approach, we demonstrate a 5 to 25-fold improvement in throughput compared to previous state-of-the-art. ...
Acknowledgements Support is gratefully acknowledged from the National Science Foundation (NSF) under grants IIS-1447786 and CCF-1563880, and the Intelligence Advanced Research Projects Activity (IARPA) ...
arXiv:1611.06565v3
fatcat:ouzr3bssdnftxe6zz5nmxdow7e
GPGPU Computing
[article]
2014
arXiv
pre-print
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platforms consisting of both CPUs and GPUs. ...
Since the first idea of using GPU to general purpose computing, things have evolved over the years and now there are several approaches to GPU programming. ...
A great number of applications were ported to use the GPU and they obtain speedups of few orders of magnitude comparing to optimized multicore CPU implementations. ...
arXiv:1408.6923v1
fatcat:gnk4arot4venzp23ihw6iy6qba
Video Coding on Multicore Graphics Processors
2010
IEEE Signal Processing Magazine
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With the advances in the GPU programing tools such as thread computing and C programming interface [16] , [17] , GPUs can be efficiently utilized to perform a variety of processing tasks in addition to ...
CPU in computation-intensive tasks such as video compression/decompression [18] . ...
ACKNOWLEDGMENTS This work has been supported in part by the Innovation and Technology Commission (GHP/048/08) and the Research Grants Council (RPC07/08.EG22 and 610109) of the Hong Kong Special Administrative ...
doi:10.1109/msp.2009.935416
fatcat:lrzn7fsggzamjjb7qdpsw356zy
High Performance Canny Edge Detector using Parallel Patterns for Scalability on Modern Multicore Processors
[article]
2017
arXiv
pre-print
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In this paper we provide a high performance implementation of Canny Edge Detector using parallel patterns for improved performance and Scalability on Multicore Processors. ...
This operator involves the use of a multi-stage algorithm to detect edges in a wide range of images. ...
ACKNOWLEDGMENTS We would like to thank everyone who took part and made effort to provide all the support and infrastructure to make this work possible. ...
arXiv:1710.07745v1
fatcat:4eyjaqe3xvb4tltn363jlqegsu
An Optimization approach for Artificial Neural Network based Co-Channel-Interference Reduction Scheme using Commodity Video Cards
2018
International Journal for Research in Applied Science and Engineering Technology
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Our Optimization approach is based on a parallel algorithm for Firefly Algorithm's fitness function, and is tailor made for a GPU or a graphical processing unit, which is the main part of a video card. ...
One such example is CCI or co-channel interference, which is a result of frequency-reuse in a cellular network. Many expensive alternatives have been suggested for speeding up the processing. ...
Moreover if we use a parallel hardware like a video card for implementing an ANN we can achieve maximum speed up [8] . ...
doi:10.22214/ijraset.2018.4629
fatcat:cjlismpvprf4lcuam7lhs4ac44
State of Art IoT and Edge Embedded Systems for Real-Time Machine Vision Applications
2022
IEEE Access
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Nevertheless, the trend now is towards a System-On-Chip (SOC) processors which combine ASIC/FPGA accelerators with GPU/multicore CPUs. ...
INDEX TERMS IoT, edge machine vision systems, multicore CPU, GPU, FPGA, ASIC. ...
In [29] researchers from Intel revealed that using this tool for either Altera's Stratix V and Arria-10 or Xilinx's Zynq FPGAs, a speed-up over most existing powerful multicore CPU (i.e. ...
doi:10.1109/access.2022.3175496
fatcat:u7dp4ov5qjhxximk5xgmuigp2m
Hardware Architectures for Real-Time Medical Imaging
2021
Electronics
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This paper focuses on the evolution and the application of different hardware architectures (namely, CPU, GPU, DSP, FPGA, and ASIC) in medical imaging through various specific examples and discussing different ...
The main purpose is to provide a general introduction to hardware acceleration techniques for medical imaging researchers and developers who need to accelerate their implementations. ...
The evaluation of these GPU-based implementations demonstrated how the use of these techniques gained up to 15.9 times of speedup against a multicore CPU solution and up to about 75 times against a single-core ...
doi:10.3390/electronics10243118
fatcat:ek4yfnw23naijkmrzhqwf5olqe
Design Flow for GPU and Multicore Execution of Dynamic Dataflow Programs
2017
Journal of Signal Processing Systems
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Experiments are performed on GPU and multicore platforms with up to 16 cores, and the results show that for high-performance applications the proposed design flow provides up to 4× higher throughput than ...
The functionality and efficiency of the proposed approach is demonstrated by a parallel implementation of a video processing application and a run-time reconfigurable filter for telecommunications. ...
This performance was measured from the complete application and includes SSD disk reads and writes, computations on CPU cores, CPU-GPU-CPU data transfers and GPU processing time. ...
doi:10.1007/s11265-017-1260-8
fatcat:kuxrz5kkujhhhoros4bglbhihq
A Highly Parallel and Scalable Motion Estimation Algorithm with GPU for HEVC
2017
Scientific Programming
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We also implemented the MLRME with CUDA, which obtained 30–60x speed-up compared to the serial algorithm on single CPU. ...
While using the local full-search method, it can exploit massive parallelism and make full use of the powerful modern many-core accelerators, such as GPU and Intel Xeon Phi. ...
As for the multicore and many-core systems with powerful single core, such as multicore CPU, Tile, and MIC, HEVC ME algorithm can get a fine speed-up by making full use of the various levels of parallelism ...
doi:10.1155/2017/1431574
fatcat:54vg5xu3nfdzrkkuqpsn5dcfy4
A GPU vs CPU performance evaluation of an experimental video compression algorithm
2015
2015 Seventh International Workshop on Quality of Multimedia Experience (QoMEX)
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The ever increasing demands for using video compression algorithms in a wide range of applications necessitate the use of processing components that boost the speed and quality of the video compression ...
This paper examines and evaluates the performance benefits of using the GPU over the CPU for an experimental video compression algorithm. ...
ACKNOWLEDGMENT This work was partially supported by the National and Kapodistrian University of Athens Special Account of Research Grants. ...
doi:10.1109/qomex.2015.7148134
dblp:conf/qomex/KatsigiannisDM15
fatcat:e3o7lzpdxfdu5ktzqlz4zh5a7i
Developing Efficient Discrete Simulations on Multicore and GPU Architectures
2020
Electronics
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We also found that current multicore CPUs with large core numbers can bring a performance very near to that of GPUs, and even identical in some cases. ...
with 48 cores, and also an NVIDIA Tesla V100 GPU, both running on Amazon Web Server (AWS) Cloud; and on a consumer-oriented platform, using an Intel Core i9 9900k CPU and an NVIDIA GeForce GTX 1050 TI ...
Even with these ratios, it is evident that a current multicore CPU may approach GPU performance. ...
doi:10.3390/electronics9010189
fatcat:qt76737cqjc3lpvhnzthmdeelu
A Survey on Parallel Multicore Computing: Performance & Improvement
2018
Advances in Science, Technology and Engineering Systems
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Then we summarized some of the recent related works implemented using multicore architecture and show the factors that have an effect on the performance of multicore parallel architecture based on their ...
This paper gives an overview about the evolution of the multicore architecture with a comparison between single, Dual and Quad. ...
The main contribution of the work is the enhancing in speed of the algorithm when using a hybrid system with multicore CPU and GPUs (graphics processing unit that is composed of hundreds of cores) with ...
doi:10.25046/aj030321
fatcat:3ukxkswjsfcsrbo7fubw26s5im
Advanced 2D Rasterization on Modern CPUs
[chapter]
2013
Applied Information Science, Engineering and Technology
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Because of the dedicated hardware visualization has been significantly accelerated and today's software uses only the GPU for rasterization. ...
Besides the graphical devices, the central processing unit (CPU) has also made remarkable progress. Multi-core architectures and new instruction sets have appeared. ...
In a technological sense, the card was a hybrid between the multi-core CPUs and GPUs. ...
doi:10.1007/978-3-319-01919-2_5
fatcat:ikubpamonng7lhtqj7drufiste
Highly Parallel Rate-Distortion Optimized Intra-Mode Decision on Multicore Graphics Processors
2009
IEEE transactions on circuits and systems for video technology (Print)
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In this paper, we consider the scenario where software-based video encoding is performed on personal computers or game consoles, and investigate how multicore graphics processing units (GPUs) may be efficiently ...
Index Terms-Graphics processing unit, greedy approach, multicore, parallel processing, rate-distortion optimized intraprediction. ...
multiview coding, scalable video coding, distributed video coding, subpixel rendering, JPEG/JPEG2000, HDR imaging, compressive sensing, halftone image data hiding, GPU-processing, and software-hardware ...
doi:10.1109/tcsvt.2009.2031515
fatcat:3nomsmpc6vfqrkdllny6jd5tom
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