Me võtame vastu krüptoraha — nii saab teie hoitav krüptoraha osta päris riistvara.Makske krüptorahaga, kulutage seda päris riistvarale. Tasuta kindlustatud tarne kogu maailmas, üle 399 $. Lihtsad, kaubamärgita väliskarbid, saadetud Saksamaalt.Tasuta kindlustatud tarne üle 399 $. Teie kurss lukustatakse 30 minutiks kohe, kui kassa avaneb.Kurss lukustatud 30 minutiks. Iga toode on pitseeritud, selle seerianumber on kontrollitud ja sellel kehtib 24-kuuline garantii.Pitseeritud, 24-kuulise garantiiga.

Hinnavaatlus Logi sisse
HP Tesla V100 16GB HBM2 PCIe graphics card with single 8-pin power connector

HP

HP NVIDIA Tesla V100 16GB HBM2 workstation graphics card Q2N68A

SKU CH-19MS-FKXC0

Delivers 16 GB HBM2 memory for AI and HPC workloads over a PCIe 3.0 x16 interface

  • GPUTesla V100
  • Memory TypeHBM2
  • 16GB HBM2 memory accelerates large-model training
  • 250W TDP fits standard workstation power budgets
  • PCIe 3.0 x16 interface integrates with existing servers
  • DirectX 12 and OpenGL 4.6 support professional visualisation
  • CUDA 7.0 enables GPU compute workloads

HP Tesla V100 16GB HBM2 compute card

This HP workstation graphics card carries an NVIDIA Tesla V100 GPU with 16GB of HBM2 memory. It is built for double-precision compute, AI training and high-performance simulation workloads. The board uses a PCIe 3.0 x16 interface and draws up to 250W through a single 8-pin power connector. It targets data-centre and workstation users who need dense memory bandwidth in a standard expansion slot.

Suited for dense GPU compute.

Engineers running CUDA 7.0 kernels, OpenCL 3.0 or Vulkan 1.2 workloads will benefit from the high-bandwidth memory and 250W thermal envelope. The card also supports DirectX 12 and OpenGL 4.6 for visualisation tasks. Buyers who need only display output or single-precision gaming performance should look at something else. Systems without a 250W power budget or a free 8-pin connector cannot use this board.

16GB HBM2 memory capacity

The 16GB HBM2 frame buffer is the specification that decides fit. It determines the maximum model size, dataset tile or simulation domain that fits in GPU memory without paging. Workloads exceeding this capacity will spill to host memory and lose performance. Check your application memory footprint against the 16GB limit before purchasing.

Põhijooned

  • 16GB HBM2 memory accelerates large-model training
  • 250W TDP fits standard workstation power budgets
  • PCIe 3.0 x16 interface integrates with existing servers
  • DirectX 12 and OpenGL 4.6 support professional visualisation
  • CUDA 7.0 enables GPU compute workloads

Tehnilised andmed

GPUTesla V100
Memory TypeHBM2

Küsimused selle toote kohta

How is the PCIe 3.0 x16 card installed and what step is often missed?

Insert the card into a PCIe 3.0 x16 slot and connect the 1x 8-pin power connector; the step often missed is ensuring the power cable is fully seated before booting.

What maintenance or replacement will the 16GB HBM2 card need later?

The 250W TDP means dust buildup on the heatsink will raise temperatures; clean the fins and fan annually and replace thermal paste if temperatures exceed safe limits.

What limit appears first under sustained compute load?

The 250W power limit is reached first; the GPU will throttle clocks to stay within the 1x 8-pin connector's delivery capacity during long Cuda workloads.

Veel samast osakonnast

Kliendid võrdlesid neid ka

Sama osakond, sama kassa — kaheksa krüptovaluutat ja 30-minutiline kursilukk.