NVIDIA – Jetson AGX Xavier – Kit per sviluppatori (32 GB)

(5 recensioni dei clienti)
  • Versione aggiornata con 16 GB di memoria aggiuntiva per un totale di 32 GB di memoria LPDDR4X a 256 bit.
  • NVIDIA Jetson Xavier è un computer IA per macchine autonome con le prestazioni di una workstation GPU in meno di 30W
  • Il kit per sviluppatori con modulo Jetson Xavier e scheda di supporto di riferimento è il modo più veloce per iniziare la prototipazione con robot, droni e altre macchine autonome
  • Tipo di sistema Ram: Ddr. Dram

3.149,75 

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SKU: 72476195 Estimated delivery:1 day

Promozione

  • Versione aggiornata con 16 GB di memoria aggiuntiva per un totale di 32 GB di memoria LPDDR4X a 256 bit.
  • NVIDIA Jetson Xavier è un computer IA per macchine autonome con le prestazioni di una workstation GPU in meno di 30W
  • Il kit per sviluppatori con modulo Jetson Xavier e scheda di supporto di riferimento è il modo più veloce per iniziare la prototipazione con robot, droni e altre macchine autonome
  • Tipo di sistema Ram: Ddr. Dram
Marca

‎nVidia

Produttore

‎NVIDIA Corporation

Modello

‎945-82972-0040-000

Nome modello

‎Jetson AGX Xavier

Dimensioni prodotto

‎10,67 x 10,67 x 10,16 cm, 1,67 kg

Numero modello articolo

‎945-82972-0040-000

Anno modello

‎2020

Numero articolo

‎945-82972-0040-000

Dimensioni RAM

‎32 GB

Capacità di memoria

‎32 GB

Dimensioni della memoria flash installata

‎32 Modificatore sconosciuto

Dimensioni memoria RAM installata

‎32 GB

Dimensioni massima memoria RAM

‎1 GB

Tipologia di memoria computer

‎DDR DRAM

Dimensioni Hard-Disk

‎32 GB

Interfaccia Hard-Disk

‎Solid State

Velocità di rotazione disco rigido

‎1 Rivoluzioni al minuto

Sistema operativo

‎Linux

Marchio processore

‎NVIDIA

Numero processori

‎1

Numero modello processore

‎8-Core ARM v8.2 64-Bit CPU, 8 MB L2 + 4 MB L3

Piattaforma Hardware

‎PC

Interfaccia Hardware

‎USB, HDMI

Dimensioni memoria scheda grafica

‎1 GB

Tipo memoria scheda grafica

‎Memoria 72-Pin EDO SIMM

Interfaccia scheda grafica

‎Integrato

Coprocessore grafico

‎NVIDIA Volta – 512 CUDA and 64 Tensor cores

Numero di articoli

‎1

Dimensione schermo

‎1 Pollici

Tipo di alimentazione

‎DC

Le pilebatterie sono incluse

‎No

Pilebatterie richieste

‎No

Tipo wireless

‎Bluetooth

Input umano interfaccia

‎Tasti

Contiene liquidi

‎No

Peso articolo

‎1,67 Kilograms

Aggiornamenti software garantiti fino a

‎sconosciuto

4.80

Based on 5 reviews
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5 reviews for NVIDIA – Jetson AGX Xavier – Kit per sviluppatori (32 GB)

  1. Avatar di S. Holton

    S. Holton

    Loaded OS to Jetson device from a VMware Workstation VMUSB. Lost connection, but manual re-connection allowed loading to continue. Running in 30 watt mode gets pretty hot – no fan included (would be nice if it had at least an attachment point and power connection for one).
    Fast and stable. good for medium training sets (haven’t tried large – may also be fine). Great compute power for the watts – just a little hot if running full-out. It is possible to run in 15 watt mode, but has less power.

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  2. Avatar di Caoyang Jiang

    Caoyang Jiang

    Overall, I like Agx Xiavier a lot better because it allows me to develop as if I am on a regular desktop. The nano is just way too slow and it even have hard time running VScode.

    I got a bad board on my first purchase. It does run but crashes randomly when left idle. The log message from the system indicates “kernel oops”. After digging through NVIDIA forum, I was sure I got a lemon. In addition to crash problem, the fan is making an random “clicking” noise. At first I am not sure if this is a typical thing for PWM fans but after I made my second purchase I know for sure that is abnormal. If your fan does not produce a consistent sound, something might be wrong.

    Here is my advice to make sure your board is good. After you receive the product, load the OS, attach internet, open a browser text editor or something, and let it sit for at least 6 hours or more (over night is better). After that, if there is no sign of rebooting, then you should be good to go. If you do notice rebooting, check if there is any kernel crash file under “/var/log”. Open crash file and search for “kernel oops”. If it does show up, don’t waste your time and just return the product.

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  3. Avatar di Kevin Goss

    Kevin Goss

    First, I own a few Jetson products. I have a few Nanos and they are great for the price, but as I am using python and tensorflow, it takes a TON of RAM and starts a lot of processes (duplicating the RAM usage). Not sure what is going on, but that is a tensorflow problem, not an Nvidia problem. I bought this unit to run many AI models in parallel, and with the memory issues I needed a lot of RAM. If you have low memory usage and are not training models with the device, go with one of the cheaper Jetsons. The Nano is a great value and does AI prediction extremely well. I am using a tornado server and am evaluating three networks in less than 50ms.

    I am not a typical use case for this device. I wouldn’t say this is a bad buy, but unless you need the RAM, go with the lower models which are amazing for the price. Train your models on a 2070 or higher (if you want speed of the tensor cores).

    UPDATE: I am now running a docker swarm with the Nanos and the Xavier. I got the RAM under control and my findings are this: for simple AI prediction I am getting about 2x the performance of the Nanos and double the RAM usage (as TF starts processes by core count and this is 8 vs 4 on Nano). For my small neural networks, this is overkill. I still think this is an amazing device, I just don’t require the power at this time. This unit does get very warm. Also, it does NOT auto power on when you have an electrical event. There is a way to jumper some pins to get it to auto power on but I haven’t done it yet. If you are training networks or doing video AI this is the Jetson for you. If you are doing less frequent prediction and don’t need the RAM, get the NX.

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  4. Avatar di D. S. Bierly

    D. S. Bierly

    Kind of silly even having reviews on these Jetson products. It’s Nvidia Jetson. Great stuff. It is what it is. If you’re not an engineer and don’t know what this is for already, don’t buy one! The negative reviews on these products are hysterical. Nvidia did a super job designing this hardware, it comes complete with solid examples and support, I’m a hardware systems guy, not software, and I still got it up and running without any issues and was able to build and benchmark their examples on the CUDA cores. I was able to build and run an existing FFTW benchmark that uses the Linux cores, and then compare that to the CUDA cuFFT examples to see the improvement–really awesome and impressive product!

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  5. Avatar di Juergen Hench

    Juergen Hench

    Solides Entwicklungskit mit gutem Funktionsumfang auf Basis von Ubuntu 18.04 (für aarch64). Achtung: KEIN PC. Die meiste Software muss ab Quellcode kompiliert werden. Nur geeignet für Entwickler, die bereits mit SoCs Erfahrung haben.

    Viel hilfereiche Information auf den NVIDIA Entwicklerforen. Das mitgelieferte Betriebssystem “Jetpack” ist z.B. in der Lage, R und die CRAN Pakete fast ohne Besonderheiten zu kompilieren. Probleme treten nur auf, wenn Compileroptionen spezfisch für andere Prozessoren in den Build-scripts festgeschrieben wurden. So z.B. einige Pakete von Bioconductor nur nach Modifikation der Compileroptionen zu kompilieren.

    Hat tatsächlich die Leistung einer GPU-ausgestatteten “Workstation”. Läuft bei gut eingestellter Lüftung monatelang stabil, auch unter Last kein Überhitzen. Zahlreiche Erweiterungsmöglichkeiten, funktionieren alle. Sicherlich interessant für alle, die die CPU/GPU Code entwickeln möchten.

    Das Developer kit ist auch für den produktiven Einsatz geeignet – z.B. in Laborumgebungen.

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