NVIDIA L40S GPU

With 48GB of GDDR6 memory, the NVIDIA L40S GPU provides sufficient capacity to handle large datasets and complex AI models.

For example, in the financial sector, extensive datasets with transaction data can be stored in memory, enabling real-time fraud detection and risk analysis. This is also crucial for scientific research, such as climate modeling, where enormous amounts of data need to be continuously processed and analyzed. This allows researchers to make more accurate predictions and gain insights faster without constantly waiting for data transfers to and from external storage.

This extensive memory configuration ensures that the GPU can perform multiple intensive tasks simultaneously without performance drops, which is essential for companies working with intensive AI and data analysis applications.

Memory bandwidth refers to the speed at which data can be transferred between the memory and the GPU. The L40S has a bandwidth of 864 GB/s.

For example, when simulating a large climate model, the high speed of 864 GB/s means that data can be quickly sent to the GPU's processing cores, resulting in faster simulations and quicker results. This prevents bottlenecks that would otherwise occur with slower data transfer.

The L40S offers impressive performance for scientific calculations. FP64 performance refers to the speed at which the GPU can perform double-precision calculations, essential for accurate scientific simulations and analyses.

The L40S supports fast data transfer between multiple GPUs via NVLink. Although the exact NVLink bandwidth is not specified, the support for PCIe Gen4 is crucial for fast communication between GPUs and improves the scalability of AI applications.

The L40S offers up to 1,466 TFLOPS of tensor calculations, utilizing Ada Lovelace Tensor Cores. This technology accelerates AI calculations, essential for deep learning and machine learning tasks, making the L40S ideal for intensive AI workloads.

The L40S is based on the Ada Lovelace architecture. This offers improved performance and efficiency compared to previous generations. This means that companies can benefit from the latest technological advancements for their AI and graphical applications, such as faster computing power and improved energy efficiency.