HPE 688982-001 PCIE 8GB Graphics Card Module Nvidia Tesla Bulk

Graphics processing units (GPUs) have become an essential component in modern computing, with applications spanning from gaming and video editing to scientific simulations and artificial intelligence. The NVIDIA Tesla K10 Dual GPU PCIe Module, specifically the 688982-001 model, is a high-performance graphics card designed to meet the demands of various industries. In this description, we will delve into the intricate details of the 688982-001 NVIDIA Tesla K10, exploring its specifications, features, and applications.

• Model Number: 688982-001 The 688982-001 is the specific model number of the NVIDIA Tesla K10 Dual GPU PCIe Module.
• GPU Architecture The Tesla K10 features the Kepler architecture, which was a significant advancement in GPU technology when it was first introduced. Kepler GPUs offer higher performance, energy efficiency, and advanced computing capabilities compared to their predecessors.
• Dual GPU Configuration One of the standout features of the Tesla K10 is its dual GPU configuration. This means it houses two separate GPUs on a single graphics card, providing double the computational power for tasks that can be parallelized across multiple GPUs.
• Graphics Memory (GDDR5 SDRAM) The 688982-001 Tesla K10 comes with 8GB of GDDR5 (Graphics Double Data Rate 5 Synchronous Dynamic Random-Access Memory) video memory. GDDR5 is a type of memory designed for high-speed graphics processing, making it ideal for graphics-intensive applications.
• Total Memory Capacity The Tesla K10 features a total memory capacity of 8192 MB, which is equivalent to 8GB. This memory is shared between the two GPUs and is used for storing textures, frames, and other data required for rendering.
• Memory Bandwidth The graphics card boasts a memory bandwidth of 320 GB/s. Memory bandwidth is crucial for the rapid exchange of data between the GPU and the video memory, ensuring smooth and responsive graphics performance.
• Power Consumption The 688982-001 Tesla K10 requires 300 watts of power to operate at full capacity. It features a power-efficient design, but it's essential to ensure your system's power supply can support this level of power consumption.
• Power Connectors The Tesla K10 features two 8-pin power connectors, providing the necessary power for the graphics card. It is essential to have a power supply unit with compatible connectors to ensure proper operation.

• High-Performance Computing The NVIDIA Tesla K10 is not just a standard gaming graphics card. It is designed for high-performance computing tasks, including scientific simulations, data analysis, and artificial intelligence applications. Its dual-GPU configuration and large memory capacity make it a powerful choice for parallel processing.
• Kepler Architecture The Kepler architecture, featured in the Tesla K10, offers several improvements over previous GPU architectures, such as Fermi. It provides better performance per watt, making it an energy-efficient option for compute-intensive workloads.
• GPU Virtualization The Tesla K10 supports GPU virtualization, which allows multiple virtual machines to share a single physical GPU. This feature is valuable in server environments, where different users or workloads require access to GPU resources.
• ECC Memory Error-Correcting Code (ECC) memory is an essential feature for applications where data integrity is critical. The Tesla K10 supports ECC memory, which can detect and correct errors in memory, ensuring the accuracy of computational results.
• Multi-GPU Scalability With two GPUs on a single card, the Tesla K10 offers impressive scalability. It can be used in multi-GPU configurations, allowing users to harness even more computational power by combining multiple Tesla K10 cards in a single system.
• CUDA Technology The Tesla K10 is compatible with NVIDIA's CUDA (Compute Unified Device Architecture) technology, which enables developers to harness the power of the GPU for parallel processing. CUDA is widely used in scientific and high-performance computing applications.
• Double-Precision Performance Double-precision performance is crucial for scientific simulations and other precision-critical tasks. The Tesla K10 offers double-precision floating-point performance, ensuring accurate results in applications that require it.
• GPU Boost GPU Boost is a feature that dynamically adjusts the GPU clock speed based on the workload, ensuring that the GPU operates at its peak performance while staying within safe temperature and power limits.
• Active Cooling To maintain optimal operating temperatures, the Tesla K10 is equipped with an active cooling solution. This fan-based cooling system helps dissipate heat generated during intense computations.

• Scientific Research The NVIDIA Tesla K10 is an ideal choice for scientific research applications that involve complex simulations, such as weather forecasting, molecular modeling, and astrophysics. Its high-performance computing capabilities and ECC memory ensure accurate results.
• Data Analysis Data analysis tasks, especially those related to big data and machine learning, can benefit from the parallel processing power of the Tesla K10. It accelerates data processing, enabling faster insights and decision-making.
• Artificial Intelligence Deep learning and neural network training require significant computational power. The Tesla K10 is well-suited for AI applications, including image and speech recognition, natural language processing, and autonomous vehicle development.
• Virtual Desktop Infrastructure (VDI) In VDI environments, the Tesla K10 can be used to provide GPU acceleration for virtual desktops, improving the user experience and enabling graphics-intensive applications to run smoothly within virtual machines.
• Content Creation Video editing, 3D rendering, and animation production demand powerful GPUs. The Tesla K10's dual-GPU configuration and high memory capacity can significantly reduce rendering times in creative workflows.
• Cloud Computing Many cloud service providers use NVIDIA Tesla GPUs, including the K10, to offer GPU-accelerated cloud computing services. This enables customers to access high-performance computing resources on demand.
• Oil and Gas Exploration The energy industry benefits from the Tesla K10's computational power for tasks such as seismic data analysis, reservoir modeling, and drilling simulations. These demanding applications require the GPU's parallel processing capabilities.
• Finance In the financial sector, the Tesla K10 can be used for risk analysis, algorithmic trading, and portfolio optimization. These applications rely on the card's ability to process vast amounts of financial data efficiently.

• PCIe Interface The Tesla K10 is designed to be installed in a PCIe (Peripheral Component Interconnect Express) slot on a compatible motherboard. It is essential to ensure that your system has a compatible PCIe slot available for installation.
• Operating System Support The Tesla K10 is compatible with various operating systems, including Linux and Windows. However, for optimal performance, it is recommended to use a Linux-based system with NVIDIA's proprietary drivers, which are well-optimized for GPU compute workloads.
• Power Supply Due to its 300-watt power consumption, the Tesla K10 requires a power supply unit (PSU) that can provide sufficient power. The card's two 8-pin power connectors must be connected to the PSU using compatible cables.
• System Configuration The Tesla K10 is primarily intended for use in server environments and workstations designed for high-performance computing. It is essential to ensure that your system's configuration is compatible with the card's physical size and power requirements.

Benchmarks and Performance

To evaluate the real-world performance of the NVIDIA Tesla K10, it is essential to consider benchmark results in various applications and scenarios. The performance of the Tesla K10 can vary significantly depending on the specific workload and software optimization. Below are some benchmark results for reference:

• LINPACK Benchmark The LINPACK benchmark measures the floating-point performance of a system. In this benchmark, the Tesla K10 has shown impressive results, making it suitable for HPC (High-Performance Computing) applications.
• Caffe Deep Learning Framework In deep learning applications, the Tesla K10 has been tested with the Caffe deep learning framework. It demonstrated substantial speedup compared to CPU-based solutions in tasks like image classification and object detection.
• Molecular Dynamics Simulation Molecular dynamics simulations are widely used in scientific research. The Tesla K10 has proven its worth in these simulations, offering accelerated performance in studying molecular structures and interactions.
• Computational Fluid Dynamics (CFD) CFD simulations are used in various industries, including aerospace and automotive engineering. The Tesla K10 can significantly reduce simulation times, aiding engineers in optimizing designs and solving complex fluid dynamics problems.
• Financial Modeling In financial applications, the Tesla K10 is capable of rapidly processing complex financial models and simulations. This is crucial for making timely decisions in trading and risk management.

It's important to note that the Tesla K10's performance in these benchmarks may vary depending on factors such as software optimization, system configuration, and the specific workload. Users should conduct their own benchmarking for their particular use cases to determine the card's performance in their environment.

• Manufacturer: HPE
• Part Number or SKU# 688982-001
• Product Type: Video Card

• Form Factor: PCIe
• Graphics Memory: 8GB
• Graphics Memory Type: GDDR5 (Graphics Double Data Rate 5)

• Graphic Processor: Nvidia Tesla K10

• Base Clock: Not specified
• Boost Clock: Not specified
• Shaders Clock: Not specified
• Memory Clock: 1502 MHz
• Effective Memory Clock: 6008 MHz

• Memory Size: 8192 MB
• Memory Type: GDDR5
• Memory Bus Type: 2 x 256-Bit
• Memory Bandwidth: 320 GB/sec

• Power Draw: 300 W (maximum, actual usage may vary)
• Minimum Required PSU: 650 W
• Power Connectors: 2 x 8-Pin

• Operating Temperature: Not specified
• Storage Temperature: Not specified
• Maximum Temperature: Not specified

Noise Level

• Noise Level: Not specified
• Idle Noise Level: Not specified

Memory/Technology

• Installed Memory: 8 GB
• Memory Technology: GDDR5 SDRAM

In summary, the NVIDIA Tesla K10 Dual GPU PCIe Module, specifically the 688982-001 model, is a powerful graphics card designed for high-performance computing. With its dual-GPU configuration, ECC memory support, and impressive computational capabilities, it is well-suited for a wide range of applications, including scientific research, data analysis, artificial intelligence, and more.

While it may not be the latest model in NVIDIA's GPU lineup, the Tesla K10 continues to be a valuable asset for industries and professionals who require significant computing power. Its compatibility with GPU virtualization, multi-GPU scalability, and support for CUDA technology make it a versatile choice for various use cases.

However, potential users should ensure that their system meets the necessary requirements, including a compatible PCIe slot and an adequate power supply unit. It's also essential to consider benchmarking the Tesla K10 for specific workloads to evaluate its performance in real-world scenarios.

The NVIDIA Tesla K10, with its dual GPUs, Kepler architecture, ECC memory, and high memory bandwidth, remains a viable option for professionals and organizations looking to accelerate their computational workloads and benefit from GPU-accelerated computing. It continues to play a vital role in advancing scientific research, data analytics, artificial intelligence, and other compute-intensive fields.