NVIDIA's Tesla K80 GPU
The NVIDIA Tesla K80 GPU is a dual-GPU accelerator designed for high-performance computing (HPC) and deep learning workloads, introduced in November 2014. It features two GK210 GPUs based on NVIDIA’s Kepler architecture, providing a total of 24GB of GDDR5 memory and 4,992 CUDA cores. The K80 delivers up to 8.73 teraFLOPS of single-precision performance, making it a powerful solution for scientific simulations, financial modeling, and large-scale data analytics. Its dual-GPU design allows for increased parallelism, enabling it to handle complex computations with high efficiency. https://en.wikipedia.org/wiki/Nvidia_Tesla
A key innovation in the Tesla K80 is its GPU Boost 2.0 technology, which dynamically adjusts clock speeds to maximize performance based on the application’s workload and thermal conditions. This feature ensures optimal utilization of the GPU, allowing it to adapt to a variety of computational tasks while maintaining GPU energy efficiency. The K80 also offers advanced memory bandwidth, with up to 480 GB/s per GPU, making it suitable for memory-intensive applications such as modeling and genomics research. https://www.nvidia.com/en-us/data-center/tesla-k80/
The NVIDIA Tesla K80 became a popular choice in cloud environments, with providers like AWS and Google Cloud offering K80-based instances for AI and HPC tasks. Although later replaced by more advanced GPUs like the Tesla P100 and Tesla V100, the K80 remains a reliable and cost-effective option for many workloads. Its legacy lies in demonstrating the potential of GPUs for scientific computing and establishing a foundation for future GPU-accelerated architectures. https://aws.amazon.com/ec2/instance-types/p2/