NVIDIA Tesla K80 24GB GDDR5 GPU Accelerator Graphics Card | High-Performance CUDA for Workstations

Overview:

The NVIDIA Tesla K80 is a powerful GPU accelerator designed specifically for data center and high-performance computing (HPC) applications. It is optimized for compute-intensive workloads such as machine learning, scientific simulations, data analytics, and rendering. With dual GPUs on a single card and a total of 24GB of GDDR5 memory, the Tesla K80 is built to handle demanding parallel processing tasks with exceptional efficiency.

Key Specifications:

• GPU Architecture: Kepler
• GPU Cores: 4,992 CUDA Cores (2,496 per GPU)
• Memory: 24GB GDDR5 (12GB per GPU)
• Memory Bandwidth: 480 GB/s (240 GB/s per GPU)
• Memory Clock Speed: 5.0 Gbps
• Peak Single Precision Performance (FP32): 8.74 Teraflops
• Peak Double Precision Performance (FP64): 2.91 Teraflops
• GPU Boost Clock: 875 MHz
• Base Clock: 562 MHz (for each GPU)
• Interface: PCIe 3.0 x16
• Power Consumption: 300W
• Form Factor: PCI Express 3.0 x16
• Thermal Design Power (TDP): 300 Watts
• Cooling: Active cooling with a blower fan to dissipate heat
• Compatibility: Compatible with workstations, servers, and high-performance computing clusters that support PCIe 3.0 slots.

Key Features:

1. Dual GPUs: The Tesla K80 includes two GPUs on a single card, making it a great option for parallel processing tasks.
2. High Memory Capacity: With a total of 24GB of GDDR5 memory (12GB per GPU), the Tesla K80 can handle large datasets, complex models, and intensive computational tasks.
3. High Bandwidth Memory: With a 480 GB/s memory bandwidth, it delivers fast access to memory, ensuring faster computation times.
4. Optimized for Compute Workloads: The Tesla K80 is engineered to accelerate scientific research, machine learning, deep learning, and complex simulations. Its architecture allows for parallel execution of tasks, which is ideal for these use cases.
5. ECC (Error-Correcting Code) Memory: The Tesla K80 supports ECC memory to reduce errors in calculations, ensuring accuracy for scientific and computational tasks.
6. CUDA Compatibility: Fully compatible with NVIDIA's CUDA programming model, allowing developers to harness the full power of parallel computing for general-purpose GPU (GPGPU) tasks.
7. NVIDIA GRID: Support for NVIDIA GRID technology allows for virtualization of GPU resources, which is ideal for enterprise environments.
8. NVLink: Supports NVIDIA's NVLink technology, enabling high-bandwidth, low-latency interconnects between GPUs for even more powerful performance in multi-GPU configurations.

Performance Benefits:

• Machine Learning and Deep Learning: The Tesla K80 can dramatically speed up the training of complex AI models with its high computational power and large memory capacity.
• Scientific Simulations: Its massive parallel processing capabilities make it ideal for simulations in fields like fluid dynamics, molecular modeling, and physics simulations.
• Data Analytics: Ideal for processing large datasets in big data analytics tasks, accelerating the analysis of complex data.

Applications:

• High-Performance Computing (HPC): The K80 is designed for scientific and engineering workloads that require intensive computing power.
• Deep Learning/AI: With support for deep learning frameworks such as TensorFlow, Caffe, and others, the Tesla K80 is suited for accelerating training of machine learning models.
• Data Analytics and Big Data: Optimized for the analysis of large datasets, making it suitable for use in data-intensive fields such as genomics, financial modeling, and predictive analytics.
• Visualization & Rendering: The Tesla K80 is well-suited for high-end visualization applications, including rendering complex 3D models and simulations.

Physical Specifications:

• Dimensions: 10.5 inches (L) x 4.4 inches (W) x 2.0 inches (H)
• Weight: Approximately 2.4 kg (5.3 lbs)
• Connectors: Dual-slot, single PCIe 3.0 x16 connector
• Display Outputs: None (designed for compute rather than display tasks)

Power and Cooling:

• Power Requirements: 300W TDP, typically requiring an 8-pin PCIe power connector for adequate power supply.
• Cooling Solution: The Tesla K80 uses a blower-style fan for efficient cooling, designed to keep both GPUs within thermal limits during heavy workloads.

Summary:

The NVIDIA Tesla K80 is a high-performance GPU accelerator designed to handle the most demanding workloads in scientific computing, machine learning, data analysis, and HPC. Its dual GPUs and large memory capacity make it ideal for tasks that require vast parallel processing power, while features like error-correcting code memory and high bandwidth ensure computational accuracy and speed. It is a popular choice in enterprise environments for tasks requiring massive computational power and for large-scale machine learning and simulation applications.