Micron Technology, Inc. MT4JTF12864AZ-1G4D1 1GB DDR3 1333 Desktop RAM
- 1GB
- DDR3 1333 (PC3 1060…
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NVIDIA
Accelerates machine learning with 3072 CUDA cores and GDDR5 memory on a 384-bit bus via PCI Express 3.0 x16
The NVIDIA Tesla M40 900-2G600-0310-030 is a compute-focused graphics card built for machine learning tasks. It provides 3072 CUDA cores and GDDR5 memory connected through a 384-bit bus. The card plugs into a PCI Express 3.0 x16 slot and targets users who need dedicated acceleration for training and inference.
Under continuous load the GPU runs at a boost clock near 1140MHz while the memory operates at 6GHz. The 384-bit interface keeps bandwidth stable during long matrix operations. This steady throughput matters more than short burst speeds for typical machine learning pipelines.
The board uses a standard PCIe 3.0 x16 connector and fits most server chassis that accept full-height cards. A frequent issue is forgetting the auxiliary power cables required for the 3072-core design. Verify that the power supply delivers the necessary connectors before seating the card.
| Memory Type | GDDR5 |
|---|
The card has a boost clock of ~1140MHz and 3072 CUDA cores, indicating sustained high compute load. Expect significant heat output requiring robust server-grade cooling and a power supply rated for high-wattage PCIe 3.0 x16 operation.
You need a motherboard with a PCI Express 3.0 x16 slot, a power supply with sufficient wattage and PCIe power connectors, and a chassis with adequate airflow for a dual-slot passive design.
Yes, the PCI Express 3.0 x16 interface is backward compatible with older PCIe generations. It will operate at the lower generation's speed when installed in a PCIe 2.0 or 1.1 slot.
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