HPE 688982-001 Nvidia Tesla K10 8GB Video Card PCI-Express Refurbished

The 688982-001 Nvidia Tesla K10 Dual GPU PCIe Module is an 8GB graphics card that is designed to deliver high-performance graphics processing for a range of applications. In this in-depth review, we will take a closer look at the key features and specifications of this 8GB graphics card, including its GDDR5 SDRAM, 8192 MB memory, 320 Gb/sec bandwidth, 300-watt power consumption, and the 2 x 8-pin power connectors.

The 688982-001 Nvidia Tesla K10 is a graphics card manufactured by Nvidia, a well-known and reputable company in the field of graphics processing units (GPUs). Nvidia is known for producing high-quality graphics cards that are widely used in various industries, including gaming, scientific computing, and artificial intelligence.

The Nvidia Tesla K10 is built on the Kepler architecture, which was a significant advancement in GPU technology when it was first introduced. Kepler architecture brought several improvements over its predecessor, Fermi, including higher energy efficiency and better performance per watt. This architecture is well-suited for compute-intensive workloads and has made the Nvidia Tesla K10 a popular choice in data centers and high-performance computing clusters.

The 688982-001 Nvidia Tesla K10 is equipped with 8GB of GDDR5 SDRAM (Graphics Double Data Rate 5 Synchronous Dynamic Random-Access Memory). GDDR5 is a type of memory commonly used in graphics cards due to its high bandwidth and low power consumption. With 8GB of memory, the Tesla K10 can handle complex graphics and compute tasks, making it suitable for a wide range of applications.

The memory bandwidth of a graphics card is a crucial factor in determining its performance, especially in tasks that involve large amounts of data transfer. The 688982-001 Nvidia Tesla K10 boasts an impressive 320 Gb/sec memory bandwidth, which allows for fast data access and manipulation. This high memory bandwidth is essential for tasks such as scientific simulations, machine learning, and 3D rendering.

Power consumption is a critical consideration when choosing a graphics card, particularly for users who need to balance performance with energy efficiency. The 688982-001 Nvidia Tesla K10 has a power consumption of 300 watts, which is relatively high compared to some consumer-grade graphics cards but is in line with the requirements of many data centers and professional computing applications.

To supply the required power to the 688982-001 Nvidia Tesla K10, the card is equipped with 2 x 8-pin power connectors. These connectors are essential for delivering the necessary power to the card for it to function properly. It's important for users to ensure that their power supply unit (PSU) has the appropriate connectors and wattage to support the Tesla K10.

One of the standout features of the Nvidia Tesla K10 is its dual GPU (Graphics Processing Unit) design. This means that the card actually contains two separate GPUs on a single PCB (Printed Circuit Board). Each GPU is capable of processing graphics and computing tasks independently, effectively doubling the card's performance potential. This dual GPU design is particularly advantageous for applications that can take advantage of parallel processing, such as scientific simulations and deep learning.

The 688982-001 Nvidia Tesla K10 is not a typical graphics card for gaming or everyday consumer use. Instead, it is designed for specific professional and high-performance computing tasks. Let's explore some of the primary use cases for this graphics card:

• Scientific Computing: The high computational power of the Tesla K10 makes it well-suited for scientific simulations, data analysis, and modeling in fields such as physics, chemistry, and climate research.
• Machine Learning and Deep Learning: Deep learning models, which require significant computational power, benefit from the Tesla K10's dual GPU design and high memory bandwidth. This card can accelerate training and inference tasks for machine learning applications.
• Data Centers: The Tesla K10 is commonly used in data centers and server farms where its performance and power efficiency are crucial for tasks such as data processing, virtualization, and cloud computing.
• 3D Rendering and CAD: Professionals working with 3D modeling, computer-aided design (CAD), and video production can leverage the Tesla K10 for faster rendering and visualization.
• High-Performance Computing (HPC): The Tesla K10 is a reliable choice for high-performance computing clusters and supercomputers. It can handle complex scientific calculations and simulations efficiently.
• Virtual Desktop Infrastructure (VDI): In VDI environments, the Tesla K10 can provide the necessary graphics performance for multiple virtual desktops, enhancing the user experience.

Compatibility and System Requirements

Before purchasing and installing the 688982-001 Nvidia Tesla K10, it's essential to ensure that your system meets the necessary compatibility and system requirements. Here are some key considerations:

• PCIe Slot: The Tesla K10 uses a PCIe (Peripheral Component Interconnect Express) interface and requires an available PCIe slot on your motherboard. Make sure your motherboard has the appropriate slot for this card.
• Power Supply: As mentioned earlier, the card requires a power supply with 2 x 8-pin connectors and sufficient wattage to support a 300-watt GPU. Verify that your power supply can meet these requirements.
• Operating System: The compatibility of the Tesla K10 with your operating system is crucial. Ensure that the drivers and software necessary for your specific application are available and compatible with your operating system.
• System Cooling: High-performance GPUs can generate a significant amount of heat. Ensure that your system has adequate cooling to prevent overheating and maintain stable performance.

Performance and Benchmarks

To gauge the performance of the 688982-001 Nvidia Tesla K10, it's common practice to rely on benchmark tests. These tests provide objective measurements of the card's capabilities and help users understand how it compares to other graphics cards. Keep in mind that the Tesla K10 is primarily designed for professional and scientific computing tasks rather than gaming, so benchmark results may vary.

• SPECviewperf: SPECviewperf is a benchmark that assesses the performance of graphics cards in professional applications like 3D rendering and visualization. The Tesla K10 typically scores well in these benchmarks, showcasing its capabilities for professional workloads.
• TensorFlow and PyTorch: For machine learning and deep learning tasks, popular deep learning frameworks like TensorFlow and PyTorch can be used to measure the Tesla K10's performance. Benchmarks involving neural network training and inference can give you a sense of how efficiently the card handles these workloads.
• Compute Benchmarks: General-purpose computing benchmarks, such as those that test floating-point performance and memory bandwidth, can provide insights into the Tesla K10's capabilities for scientific computing and data processing.
• Real-World Applications: While benchmark tests are valuable, it's also essential to consider real-world applications relevant to your specific use case. Running your own tests with the software and workflows you plan to use can provide the most accurate performance assessment.

Considerations and Alternatives

When evaluating the 688982-001 Nvidia Tesla K10 for your specific needs, consider the following factors:

• Application Requirements: Ensure that the Tesla K10 aligns with the requirements of your specific applications. If you're primarily interested in gaming, consumer-grade GPUs may be more cost-effective and better suited for that purpose.
• Budget: Professional-grade GPUs like the Tesla K10 can be relatively expensive. Determine whether your budget allows for such an investment and whether the card's performance justifies the cost for your intended tasks.
• Future Needs: Consider your future computing needs. If your workloads are expected to grow in complexity, investing in a high-performance GPU like the Tesla K10 may be a wise choice to ensure scalability.
• Alternatives: Depending on your use case, you might want to explore alternative Nvidia GPUs or GPUs from other manufacturers to find the best fit for your requirements.

• Manufacturer: HPE
• Part Number or SKU# 688982-001
• Product Type: Tesla K10 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 688982-001 Nvidia Tesla K10 Dual GPU PCIe Module 8GB graphics card is a powerful and versatile solution designed for professional and high-performance computing tasks. With its dual GPU design, ample memory, high memory bandwidth, and specialized support for scientific computing and deep learning, it caters to a range of demanding applications.

While it may not be the best choice for gaming or everyday consumer use, it excels in data centers, research institutions, and industries where computational power and efficiency are paramount. Before investing in the Tesla K10, carefully assess your specific needs and budget, ensuring that it aligns with your intended use cases and system requirements. With the right setup, this graphics card can significantly enhance your computing capabilities for a variety of compute-intensive tasks.