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Full-length passive GPU card with silver heatsink and single 8-pin power connector

NVIDIA

NVIDIA Tesla M40 24GB GDDR5 graphics card

SKU CH-4M8S-2AN8R

A 24 GB GDDR5 GPU with 3072 CUDA cores and 288 Gb/s memory bandwidth for machine-learning workloads

  • Memory TypeGDDR5
  • 24 GB GDDR5 memory enables large-model training
  • 3072 CUDA cores accelerate parallel compute workloads
  • 288 Gb/s bandwidth feeds data to the GPU fast
  • Passive 250 W thermal design suits dense server racks
  • PCI Express 3.0 x16 interface fits standard accelerator slots

NVIDIA Tesla M40 24GB GPU

The NVIDIA Tesla M40 is a 24GB GDDR5 accelerator built for machine-learning workloads. It delivers 3072 CUDA cores and a 384-bit memory interface running at 6GHz. The card connects through a PCI Express 3.0 x16 slot and has a thermal design power of 250W.

Passive cooling and power checks

This model uses a passive heatsink so your chassis must supply strong directed airflow across the board. Verify that the power supply can provide a dedicated 8-pin CPU connector and sustain the 250W board draw. The double-width bracket occupies two full-height expansion slots in the server.

Sustained 7 TFLOPS single precision

Under continuous load the GPU maintains its ~1140MHz boost clock to deliver 7 TFLOPS of FP32 throughput. Double-precision performance runs at 0.21 TFLOPS with a 1/32 ratio. The 288 Gb/s memory bandwidth and 24GB frame buffer keep large datasets resident during long training runs.

Besonderheiten

  • 24 GB GDDR5 memory enables large-model training
  • 3072 CUDA cores accelerate parallel compute workloads
  • 288 Gb/s bandwidth feeds data to the GPU fast
  • Passive 250 W thermal design suits dense server racks
  • PCI Express 3.0 x16 interface fits standard accelerator slots

Technische Daten

Memory TypeGDDR5

Fragen zu diesem Artikel

Does the Tesla M40 24GB card ship with any cables or brackets, or must I buy them separately?

The card is supplied as shown in the picture; no cables or mounting brackets are included, so you will need to source an 8-pin CPU power cable and a compatible bracket for your chassis.

Should I choose this 24GB model or a smaller capacity for machine-learning workloads?

The 24GB GDDR5 frame buffer and 3072 CUDA cores give the headroom needed for larger models and batches that would not fit on a smaller card.

What does the 7 TFLOPS single-precision rating mean when the card is running in a server?

At ~1140 MHz boost clock the GM200 GPU can deliver up to 7 TFLOPS FP32 throughput, limited by the 250 W TDP and passive cooling in your airflow.

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