SK hynix HMA42GR7AFR4N-TF 16GB DDR4 2133MHz CL15 ECC Registered Dual Rank 1.2V 288-Pin Server RAM
- 16GB
- 288-Pin DDR4 SDRAM
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NVIDIA
Workstation graphics card with 256 CUDA cores and 256-bit GDDR5 memory for professional 3D workloads
The NVIDIA Quadro 4000 is a workstation graphics card built for professional 3D workflows. It delivers 256 CUDA cores and 2GB of GDDR5 memory across a 256-bit interface. The card connects via a PCI Express 2.0 x16 slot and supports DirectX 11 and OpenGL 4.4. It is suited for CAD, DCC and visualisation tasks that rely on certified drivers.
Engineers, architects and designers who need ISV-certified driver support for professional applications will benefit from this hardware. It provides two DisplayPort outputs and one DVI connector for multi-display setups. Buyers who require more video memory for large models or higher compute performance for GPU rendering should consider other options. The PCI Express 2.0 interface may limit throughput on newer platforms.
The 2GB GDDR5 memory capacity is the specification that determines suitability for a given workload. It handles moderate assembly sizes and texture datasets in supported professional applications. Larger scenes, high-resolution textures or multi-application GPU acceleration will exceed this buffer. Verify your software’s memory requirements before purchase.
| Brand | NVIDIA |
|---|---|
| Model | Quadro 4000 |
| Interface | PCI Express 2.0 x16 |
| GPU | Quadro 4000 |
| CUDA Cores | 256 |
| Memory Interface | 256-Bit |
| Memory Type | GDDR5 |
| DirectX | DirectX 11 |
| OpenGL | OpenGL 4.4 |
| DisplayPort | 2 |
| DVI | 1 |
Insert the full-height card into a PCI Express 2.0 x16 slot, secure the bracket screw, then attach the required auxiliary power connector; the step most often missed is connecting that power cable.
Periodically remove dust from the heatsink and fan with compressed air; if the fan becomes noisy or stops spinning, replace the fan assembly to maintain cooling.
The 2 GB GDDR5 frame buffer fills before the 256 CUDA cores saturate, so memory capacity is the first bottleneck in extended workloads.
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