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Books on the topic 'NVIDIA'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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1

Kurniawan, Agus. IoT Projects with NVIDIA Jetson Nano. Apress, 2021. http://dx.doi.org/10.1007/978-1-4842-6452-2.

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2

Zielgruppenanalyse - Nvidia GeForce-Grafikkarten: Nvidia GeForce Grafikkarten im Performance- und High-End-Segment. GRIN Verlag GmbH, 2011.

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3

Ruiz, José Marcos Arroyo. Fundamentos básicos de NVIDIA Jetso Nano. Marcombo, 2022.

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4

Dagg, Michael. NVIDIA GPU Programming: Massively Parallel Programming with CUDA. Wiley & Sons, Incorporated, John, 2012.

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5

Dagg, Michael. NVIDIA GPU Programming: Massively Parallel Programming with CUDA. Wiley & Sons, Incorporated, John, 2013.

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6

Dagg, Michael. NVIDIA GPU Programming: Massively Parallel Programming with CUDA. Wiley & Sons, Incorporated, John, 2012.

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7

Meier, Jan. GPU Powered VDI: Virtual Desktops with NVIDIA GRID. Independently Published, 2018.

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8

Jons, Kingston. Nvidia Shield TV Pro User Guide: The Ultimate User Guide to Master the New Nvidia Shield TV Pro in 2 Hours. Independently Published, 2020.

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9

Ltd, ICON Group, and ICON Group International Inc. NVIDIA CORP.: Labor Productivity Benchmarks and International Gap Analysis (Labor Productivity Series). 2nd ed. Icon Group International, 2000.

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10

Ltd, ICON Group, and ICON Group International Inc. NVIDIA CORP.: International Competitive Benchmarks and Financial Gap Analysis (Financial Performance Series). 2nd ed. Icon Group International, 2000.

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11

IoT Projects with NVIDIA Jetson Nano: AI-Enabled Internet of Things Projects for Beginners. Apress L. P., 2020.

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12

Stocks and Cryptos Watchlist and Investing Experience: 2021-2022 with Nvidia, Amazon, Ethereum, Bitcoin, Polkadot, Solana, and Polygon. Independently Published, 2022.

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13

ELIV-MarketPlace 2018. VDI Verlag, 2018. http://dx.doi.org/10.51202/9783181023389.

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Alle Entwicklungen rund ums Auto und das vieldiskutierte vollautomatisierte Fahren sind sehr sehr spannend. Hier können Sie die neuesten Entwicklungen nachlesen. Inhalt (Auszüge) HAF und VAF: Anforderungen, Realisierungen und Ausblicke Artifical Intelligence in the Driver’s Seat / AI – enabling autonomous driving and transportation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1 P. de Boer, NVIDIA, USA AF und VAF: Realisierungen und Ausblicke Artificial Intelligence: Today ́s and tomorrow ́s opportunities, how do we adjust to it?. .
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14

Rucci, Enzo. Evaluación de rendimiento y eficiencia energética de sistemas heterogéneos para bioinformática. Editorial de la Universidad Nacional de La Plata (EDULP), 2018. http://dx.doi.org/10.35537/10915/66533.

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El problema del consumo energético se presenta como uno de los mayores obstáculos para el diseño de sistemas que sean capaces de alcanzar la escala de los Exaflops. Por lo tanto, la comunidad científica está en la búsqueda de diferentes maneras de mejorar la eficiencia energética de los sistemas HPC. Una tendencia reciente para incrementar el poder computacional y al mismo tiempo limitar el consumo de potencia de estos sistemas consiste en incorporarles aceleradores y coprocesadores, como pueden ser las GPUs de NVIDIA y AMD o los coprocesadores Xeon Phi de Intel. Por otra parte, las FPGAs apar
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15

Laberintos: Libro de Actividades de Nvidad Encuentra la Salida de Estos 95 Laberintos. Independently Published, 2020.

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