NVIDIA
NVIDIA Tesla M40 24GB GDDR5 0MY6DR CN-0MY6DR PG600 GPU Accelerator MY6DR USA PCI-EXPRESS
A GPU accelerator card with 24 GB GDDR5 memory and a PCI Express 3.0 interface for compute workloads
- Memory TypeGDDR5
- 24 GB GDDR5 memory handles large datasets
- PCI Express 3.0 interface provides high bandwidth
- Tesla M40 accelerator designed for compute workloads
- PG600 board revision identifies the hardware
- 30 day refund window protects the purchase
Tesla M40 24GB Accelerator
The NVIDIA Tesla M40 is a GPU accelerator card equipped with 24GB of GDDR5 memory and a PCI Express 3.0 interface. It is built for compute-intensive workloads such as deep learning training, scientific simulation and large-scale data analytics. The PG600 board design targets server and workstation environments that need sustained double-precision throughput.
Suited for dense compute; not for display output
This card suits researchers and engineers who need high memory capacity for model training or batch inference in headless servers. It is not intended for users who require video outputs for monitors, workstations with limited auxiliary power connectors, or systems that cannot accommodate a dual-slot passive design.
24GB GDDR5 memory capacity
The 24GB GDDR5 frame buffer is the specification that determines whether the M40 fits the workload. Models that need larger datasets resident in GPU memory benefit directly from this capacity, while smaller models may not require the full allocation.
Points forts
- 24 GB GDDR5 memory handles large datasets
- PCI Express 3.0 interface provides high bandwidth
- Tesla M40 accelerator designed for compute workloads
- PG600 board revision identifies the hardware
- 30 day refund window protects the purchase
Caractéristiques
| Memory Type | GDDR5 |
|---|
Questions sur cet article
What power connections does the Tesla M40 require?
The card draws power through the PCI Express 3.0 slot and onboard auxiliary connectors; a supply with sufficient wattage and the correct 8-pin or 6-pin leads is needed.
Will this accelerator fit in a standard workstation chassis?
It follows a dual-slot PCIe form factor, so verify that your case has two adjacent expansion slots and enough length clearance for a full-height board.
Which workloads benefit from the 24 GB GDDR5 memory?
Large-model inference, batch rendering and scientific compute jobs that need high memory capacity without NVLink scaling.
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