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NVIDIA Tesla M40 24GB passive GPU accelerator card with large aluminium heatsink and single 8-pin power connector

NVIDIA

NVIDIA Tesla M40 24GB GDDR5 PCIe 3.0 x16 Passive Accelerator

SKU CH-SJVW-265MD

A passive PCIe 3.0 x16 accelerator with 3072 CUDA cores, 24 GB GDDR5 memory on a 384-bit bus and 250 W TDP for machine-learning workloads

  • Memory InterfacePCI Express 3.0 x16
  • 24 GB GDDR5 memory supports large neural-network datasets
  • 3,072 CUDA cores deliver 7 TFLOPS single-precision throughput
  • 288 GB/s bandwidth feeds compute-intensive workloads
  • Passive 250 W thermal design suits dense server racks
  • PCIe 3.0 x16 interface connects to standard accelerator slots

NVIDIA Tesla M40 24GB Accelerator

This passive PCIe 3.0 x16 card targets machine-learning workloads. It delivers 3072 CUDA cores and 24GB of GDDR5 memory for large-model training and inference. A 250 W TDP requires robust server airflow. No display outputs are present.

24GB GDDR5 on 384-bit Bus

The single spec that decides fit is the 24GB frame buffer paired with a 384-bit interface at 6 GHz. That combination yields 288 GB/s bandwidth, feeding the 7 TFLOPS FP32 engine. Workloads that exceed smaller buffers will run without paging.

Dual 8-Pin Power in Dense Servers

Two 8-pin CPU power connectors supply the 250 W draw, so the PSU must provide both leads. Passive cooling moves heat into chassis airflow, freeing PCIe slots that active fans would block. The x16 electrical link matches standard server backplanes.

Points forts

  • 24 GB GDDR5 memory supports large neural-network datasets
  • 3,072 CUDA cores deliver 7 TFLOPS single-precision throughput
  • 288 GB/s bandwidth feeds compute-intensive workloads
  • Passive 250 W thermal design suits dense server racks
  • PCIe 3.0 x16 interface connects to standard accelerator slots

Caractéristiques

BrandNvidia
ModelNvidia Tesla M40
Memory InterfacePCI Express 3.0 x16

Questions sur cet article

Will the passive cooler fit in a standard server chassis?

The card uses a passive heatsink and requires forced airflow from the chassis fans; verify your server provides sufficient air velocity across the full-length, dual-slot form factor.

What auxiliary power cable is required?

The board draws up to 250 W and is fed by a single 8-pin CPU power connector; ensure your power supply includes this cable.

Can the 24 GB frame buffer handle large training batches?

With 24 GB of GDDR5 on a 384-bit bus delivering 288 GB/s bandwidth, the card can hold sizable models and batches for inference or mixed-precision training workloads.

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