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5614410
NVIDIA 900-2G414-0000-000 Tesla P4 8GB GDDR5 Inferencing Accelerator Passive Cooling
Item #:
5614410
XCD 624
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What Stands Out
High Performance
The NVIDIA Tesla P4 delivers exceptional inferencing performance with its powerful GPU architecture, enabling rapid processing for machine learning and AI applications.
Energy Efficient
With passive cooling design and optimized energy consumption, the Tesla P4 ensures reduced operational costs while maintaining high performance, making it ideal for data centers.
Versatile Compatibility
Designed for seamless integration, the Tesla P4 supports various frameworks and workloads, making it suitable for diverse applications, from deep learning to video analysis.
Product Details
- Model: 900-2G414-0000-000
- Series: Tesla P4
- Integer Operations (INT8): 22 TOPS
- GPU Memory: 8 GB
- Memory Bandwidth: 192 GB/s
- Max Power: 50W/75W
| Package Weight | 1.1 Pound |
Who Should Buy?
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AI Researchers
Perfect for AI researchers needing efficient, high-performance inference acceleration in machine learning applications and research environments.
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Data Centers
Ideal for data centers focusing on AI workloads, requiring energy-efficient, passive cooling solutions with powerful processing capabilities.
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Video Processing
A great choice for professionals in video processing, enabling swift, real-time analysis and rendering of complex visual data.
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Gaming Enthusiasts
Not suited for gamers as it lacks the necessary features to handle high-performance gaming and graphics-intensive applications.
Product Description
NVIDIA 900-2G414-0000-000 Tesla P4 8GB GDDR5 Inferencing Accelerator Passive Cooling
Have any Query? Chat with us
Customer Questions & Answers
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Question:
What is the NVIDIA Tesla P4 used for?
Answer: The NVIDIA Tesla P4 is primarily designed for deep learning inference and AI workloads. It excels in tasks where high-performance computation is required, such as image processing and video analytics. Its architecture allows it to deliver powerful acceleration while maintaining energy efficiency, making it suitable for data centers and cloud computing environments. Additionally, the Tesla P4's passive cooling design ensures quiet operation, which is ideal for configuration in rack-mounted servers or other environments where noise control is important. -
Question:
How does passive cooling work in the Tesla P4?
Answer: Passive cooling in the NVIDIA Tesla P4 involves heat dissipation without active components like fans. Instead, it uses heat sinks and efficient thermal management to maintain optimal operating temperatures. This design minimizes the need for maintenance related to fan failures and guarantees silent operation. Passive cooling is particularly beneficial in quiet settings, such as offices or studios, allowing users to focus on their tasks without noise interruptions. -
Question:
What are the key specifications of the Tesla P4?
Answer: The NVIDIA Tesla P4 features 8GB of GDDR5 memory, optimized for processing complex data sets and supporting AI model inference. It harnesses the NVIDIA Pascal architecture, offering superior performance compared to previous generations. In addition, it boasts a high-performance computing capability with Tensor Core technology, specifically designed for AI applications. This makes it a preferred choice for organizations looking to accelerate their machine learning workloads and streamline data analysis tasks. -
Question:
What type of workloads is the Tesla P4 best suited for?
Answer: The Tesla P4 is optimal for deep learning inference, computer vision applications, and high-performance computational tasks. It is particularly effective for running neural networks and processing video streams in real-time, which is essential for applications such as self-driving technology, augmented reality, and facial recognition systems. Organizations utilizing the Tesla P4 can enhance their AI capabilities and speed up processing times significantly, making it a powerful tool for developers and researchers alike. -
Question:
Can the Tesla P4 be used with existing server infrastructures?
Answer: Yes, the Tesla P4 is designed for compatibility with existing server infrastructures. It can be integrated into standard PCIe slots found in modern servers, allowing for straightforward upgrades without major overhauls. This adaptability means users can enhance the computational power of their systems easily while utilizing their current setup, making it a cost-efficient solution for businesses looking to improve their AI and machine learning performance. -
Question:
What are the benefits of using NVIDIA GDDR5 memory?
Answer: NVIDIA GDDR5 memory offers high bandwidth and optimized data transfer rates, which are crucial for handling large datasets and complex computations efficiently. With the Tesla P4 utilizing 8GB of GDDR5, users can expect faster processing times and improved performance in AI inference tasks. This memory technology enhances responsiveness and helps to reduce bottlenecks in processing, enabling organizations to execute more demanding workloads seamlessly. -
Question:
How does the Tesla P4 compare to other NVIDIA GPUs?
Answer: Compared to other NVIDIA GPUs, the Tesla P4 is specifically tailored for inferencing tasks rather than training deep learning models. While GPUs like the Tesla V100 might offer higher performance for training due to more CUDA cores and larger memory, the P4 is engineered for efficiency in inference with lower power consumption and thermal output. This specialization allows the P4 to deliver outstanding performance in real-time applications, making it a go-to choice for deploying machine learning models. -
Question:
What types of applications can benefit from the Tesla P4?
Answer: Applications that can benefit from the Tesla P4 include real-time video analytics, natural language processing, and large-scale recommendation systems. Industries like healthcare, retail, and autonomous vehicles use the performance of the Tesla P4 to enhance their AI capabilities. For instance, in healthcare, it can analyze medical images rapidly, improving diagnostic accuracy and speed. In retail, it supports personalized marketing through predictive analytics, enhancing customer experiences. -
Question:
What is the role of Tensor Cores in the Tesla P4?
Answer: Tensor Cores in the Tesla P4 play a pivotal role in accelerating deep learning computations. These specialized cores optimize matrix multiplication operations that are fundamental to neural network training and inference. By processing multiple operations in parallel, Tensor Cores expand throughput significantly, making the Tesla P4 particularly effective in handling large-scale models and datasets. This enhancement allows for more complex AI applications, leading to better performance and quicker insights. -
Question:
Where can I buy NVIDIA 900-2G414-0000-000 Tesla P4 8GB GDDR5 Inferencing Accelerator Passive Cooling in Saint Lucia?
Answer: You can buy the NVIDIA 900-2G414-0000-000 Tesla P4 8GB GDDR5 Inferencing Accelerator Passive Cooling from Ubuy in Saint Lucia. Ubuy is an excellent platform known for its extensive range of electronics and computing products, ensuring you find the right specifications and models that suit your needs. With Ubuy, you can explore different options available for the Tesla P4 and make an informed purchasing decision.
NVIDIA Graphics Cards Editorial Review
In reviewing the NVidia GPU, it appears that customer experiences vary significantly, with a recurrent theme of thermal management issues. Users have expressed frustration with the card's tendency to overheat, particularly in various server environments, including the Dell R630 and T630. Many found that adequate airflow and elevated fan speeds were necessary to stabilize temperatures, which not only generated excessive noise but also raised concerns about the GPU's overall reliability and performance. One reviewer recounted using the card under VMware for Windows Remote Desktop and noted that despite efforts to maintain an optimal cooling solution, the card Consistently thermal throttled unless fan speeds were ramped to 60% or more. This led to the conclusion that the GPU could be Considered a 'bad unit' or perhaps simply not fit for purpose in its given use case. The reviewer ultimately suggested exploring alternatives such as the T4, which they praised for its superior performance, increased memory, and advanced features like machine learning capabilities and ray tracing, all provided at a similar price point. Overall, the reception of this particular NVidia GPU has not been optimal amongst users who prioritize stable performance and quiet operation, pointing them towards other available options that promise better efficiency and functionality. **
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Pros
- Potential for integration with VMware for remote desktop applications.
- Can stabilize temperatures with significant modifications to cooling systems.
Cons
- Frequently overheats and thermal throttles under standard operations.
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Features & Benefits
- 22 TOPS for INT8 operations
- 8GB of GPU Memory
- 192 GB/s Memory Bandwidth
- 50W/75W Max Power consumption
- Low-Profile PCI Express Form Factor
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