Cisco UCSC-GPU-M10 M10 32GB GDDR5 PCI-e GPU Processor

Cisco UCSC-GPU-M10 Nvidia Tesla M10 32GB GDDR5 PCI-e GPU Accelerator Processor Overview

The Cisco UCSC-GPU-M10 Nvidia Tesla M10 32GB GDDR5 PCI-e GPU Accelerator Processor is a powerful, high-performance solution designed to meet the growing demands of modern data centers and computational workloads. It offers exceptional GPU acceleration for a range of workloads, from virtualized environments to artificial intelligence and machine learning applications. With its advanced architecture, high memory capacity, and efficient energy consumption, the Cisco UCSC-GPU-M10 stands as an ideal choice for businesses and organizations seeking to scale their computing power while maintaining a cost-effective solution.

Key Features of the Cisco UCSC-GPU-M10

Equipped with the latest Nvidia Tesla M10 architecture, this GPU processor is designed to deliver maximum performance for intensive computing tasks. Below, we break down the key features of the Cisco UCSC-GPU-M10 to help you understand its capabilities:

1. Nvidia Tesla M10 Architecture

The heart of the UCSC-GPU-M10 is the Nvidia Tesla M10, a cutting-edge GPU accelerator optimized for virtualization and high-performance computing (HPC). Featuring a robust 32GB GDDR5 memory, the Tesla M10 delivers remarkable performance for applications that demand high throughput, such as 3D rendering, simulation, and virtual desktop infrastructure (VDI).

2. High Memory Capacity: 32GB GDDR5

The Cisco UCSC-GPU-M10 comes with an impressive 32GB of GDDR5 memory, enabling the handling of large datasets and complex computations. This significant memory capacity ensures that your computing tasks run smoothly, even under heavy workloads, making it suitable for high-performance gaming, video processing, data analytics, and machine learning applications.

3. PCIe 3.0 Interface

The PCIe 3.0 interface provides faster data transfer rates, improving the overall speed and efficiency of the system. With support for PCIe 3.0, the Cisco UCSC-GPU-M10 ensures a faster connection between the GPU and the rest of the computing infrastructure, allowing for seamless data processing and accelerating workloads in real-time.

4. Efficient Energy Consumption

Despite its powerful performance, the Cisco UCSC-GPU-M10 is designed to operate with efficient energy usage, making it a cost-effective choice for enterprises looking to scale without increasing energy consumption drastically. The GPU processor offers a balance between performance and power efficiency, ensuring that businesses can optimize their data centers while keeping costs in check.

Applications and Use Cases

The Cisco UCSC-GPU-M10 Nvidia Tesla M10 is designed for a wide range of applications that require advanced computational capabilities. Below are some of the primary use cases that benefit from this GPU processor:

1. Virtual Desktop Infrastructure (VDI)

Virtual desktop infrastructure (VDI) is one of the most common use cases for the Cisco UCSC-GPU-M10. By utilizing the Tesla M10’s multi-user GPU virtualization capabilities, businesses can provide high-quality virtual desktops to users, enabling them to run demanding applications such as CAD software, 3D modeling tools, and video editing suites. This helps organizations deliver a seamless user experience for remote employees or those working from multiple devices.

2. Artificial Intelligence and Machine Learning

With its powerful processing capabilities, the Cisco UCSC-GPU-M10 is an excellent choice for artificial intelligence (AI) and machine learning (ML) tasks. The high throughput of the Tesla M10 accelerator allows for faster training of machine learning models, as well as the ability to process large datasets with ease. Whether you’re working on natural language processing (NLP), computer vision, or deep learning, the M10 GPU provides the processing power needed for these advanced tasks.

3. High-Performance Computing (HPC)

The Cisco UCSC-GPU-M10 is well-suited for high-performance computing environments, where complex simulations and data-heavy computations are required. Scientific research, financial modeling, and engineering simulations all benefit from the parallel processing capabilities of the Tesla M10 GPU, which can dramatically reduce the time required to complete complex computations.

4. Video Rendering and Content Creation

For content creators in fields like video production, animation, and 3D rendering, the Cisco UCSC-GPU-M10 can greatly speed up rendering times and improve the overall workflow. With its large memory capacity and parallel processing abilities, the GPU accelerator can render complex scenes and animations more efficiently, allowing content creators to focus more on creative tasks rather than waiting for long render times.

Benefits of Using the Cisco UCSC-GPU-M10

There are numerous benefits to integrating the Cisco UCSC-GPU-M10 Nvidia Tesla M10 GPU Accelerator Processor into your IT infrastructure. Let’s explore the key advantages:

1. Scalable Performance

The Cisco UCSC-GPU-M10 allows organizations to scale their computing infrastructure by adding multiple GPUs to their systems. This scalability is crucial for businesses that anticipate growing data processing demands and need a flexible solution that can grow with them.

2. Enhanced Virtualization Capabilities

With Nvidia’s GPU virtualization technology, the Cisco UCSC-GPU-M10 provides enhanced capabilities for running multiple virtual machines on a single physical server. This allows organizations to increase the density of virtualized workloads, reducing the need for additional hardware and improving overall infrastructure efficiency.

3. Improved Reliability and Stability

Cisco is known for its reliable and stable hardware, and the UCSC-GPU-M10 is no exception. The processor has been designed to run for extended periods under heavy workloads without compromising performance or stability, ensuring that your data center or computing environment operates smoothly.

4. Cost-Effective Solution for High-Performance Computing

By leveraging the Cisco UCSC-GPU-M10, businesses can achieve the performance of a dedicated supercomputer at a fraction of the cost. The GPU accelerator enables businesses to consolidate their workloads on fewer machines, reducing the overall footprint and the operational costs associated with running multiple physical servers.

Compatibility and Integration with Cisco UCS Servers

The Cisco UCSC-GPU-M10 is fully compatible with the Cisco Unified Computing System (UCS), providing a seamless integration for organizations already using UCS infrastructure. The UCS platform combines computing, networking, and storage into a unified system that simplifies management and accelerates business agility. The GPU processor is designed to work effortlessly within this system, delivering exceptional performance while simplifying your IT operations.

1. Simplified Management

With Cisco’s UCS Manager, businesses can manage their GPU infrastructure along with other UCS components through a single interface. This simplifies configuration, monitoring, and troubleshooting, providing a more efficient way to manage data center resources and ensuring that your GPU processors are always operating optimally.

2. Integration with Cisco UCS B-Series and C-Series Servers

The Cisco UCSC-GPU-M10 is designed to integrate seamlessly with both the Cisco UCS B-Series Blade Servers and Cisco UCS C-Series Rack Servers. This integration ensures that businesses can easily add GPU acceleration to their existing infrastructure, enhancing the performance of both blade and rack server environments without significant disruptions to operations.

Technical Specifications of the Cisco UCSC-GPU-M10

GPU Model:

• Nvidia Tesla M10

Memory:

• 32GB GDDR5

Interface:

• PCIe 3.0

Power Requirements:

• Power Consumption: 225W
• Recommended PSU: 750W

Form Factor:

• Full-height, Full-length PCIe card

Operating Temperature:

• 0°C to 55°C

Key Benefits at a Glance

• Ideal for virtualization, machine learning, and HPC applications
• Enhanced GPU virtualization with support for multiple users
• High memory capacity for handling large workloads
• Seamless integration with Cisco UCS servers
• Energy-efficient design to reduce operational costs