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- [[Category:GPU]]3 KB (466 words) - 18:20, 19 June 2019
- [[Category:GPU]]2 KB (300 words) - 18:27, 19 June 2019
- ...onal power on a [https://arstechnica.com/gadgets/2017/05/nvidia-tesla-v100-gpu-details/ massive 800 mm² die].]]7 KB (917 words) - 17:04, 24 November 2023
- .... For this reason, CNN are nowadays decently served by specialized CPU and GPU architectures, reaching very high energy efficiency per inference, and bein4 KB (651 words) - 19:10, 29 January 2021
- .... For this reason, CNN are nowadays decently served by specialized CPU and GPU architectures, reaching very high energy efficiency per inference, and bein4 KB (644 words) - 19:10, 29 January 2021
- ...from low power accelerometers you will conduct some first experiments with GPU accelerated code to come up with a set of discriminative features and desig5 KB (759 words) - 09:18, 16 September 2021
- ...onal power on a [https://arstechnica.com/gadgets/2017/05/nvidia-tesla-v100-gpu-details/ massive 800 mm² die].]]3 KB (339 words) - 15:59, 1 November 2023
- [[File:IIP_Beamspace_GPU.png|500px|thumb|Beamspace processing on GPU]] ...orms for baseband processing. Additionally, there is growing interest from GPU vendors to invest in the wireless communication industry. Hence, it is the4 KB (620 words) - 00:16, 11 January 2022
- ...ion cameras. The student will use a cutting-edge high-performance embedded GPU to acquire data from these devices and run sensor-fusion based algorithms t2 KB (349 words) - 15:53, 11 October 2021
- ...A Study of Hardware Performance Counters Selection for Cross Architectural GPU Power Modeling]</div>5 KB (688 words) - 13:51, 27 October 2022
- ...ion and machine learning framework will be applied to implement performant GPU-based simulations.4 KB (503 words) - 13:54, 30 May 2022
- ...al Neural Networks (ANN) have revolutionized many applications, enabled by GPU acceleration of machine learning algorithms. To bring machine learning to e4 KB (585 words) - 14:05, 15 February 2024
- * Compare your results to a GPU or server-class CPU implementation [11]7 KB (944 words) - 10:47, 25 January 2024
- ...e, MKL or OpenBLAS for CPU architectures and cuBLAS or cuSPARSE for NVIDIA GPU microarchitectures. Unfortunately, these libraries optimize common-use case3 KB (446 words) - 15:56, 1 May 2023
- ...stream that needs to be accessed and monitored calls for a high-speed FPGA/GPU based system with a compact, and incubator-compatible hardware design.6 KB (720 words) - 16:27, 27 September 2023
- ...tion. The parallel representation empowers training parallelism to utilize GPU devices fully, whereas the recurrent representation enables efficient O(1)6 KB (844 words) - 14:28, 18 February 2024
- ...tion. The parallel representation empowers training parallelism to utilize GPU devices fully, whereas the recurrent representation enables efficient O(1)5 KB (735 words) - 14:31, 18 February 2024
- ...found in Occamy [4], aim to rival the energy-efficiency and performance of GPU accelerators. Therefore preserving the energy-efficiency of the core is key7 KB (1,153 words) - 18:58, 21 April 2024
- ...uster. The motherboard contains two PCIe slots to hold computing cards, as GPU, network cards, or specific accelerators. Finally, SG2042 comes with an ope3 KB (459 words) - 13:24, 12 April 2024