Why Data Center GPUs Are Essential to Innovation

[Md. Abdur Rahim]

Data center graphics processing units (GPUs) are discrete accelerators that enable and enhance emerging technologies such as artificial intelligence (AI), rendering, analytics, and simulation/modeling.

To support AI, analytics, 3D rendering, and other advanced workloads, GPUs must play an expanded role in your data center environment. By augmenting CPUs with powerful parallel processing capabilities, data center GPUs help speed outcomes and accelerate innovation.

New Use Cases Require New Data Center Hardware

In the data center, GPUs are being applied to help solve today’s most complex and challenging problems through technologies such as AI, media and media analytics, and 3D rendering. Across technology segments, such as high performance computing (HPC) and visual cloud computing, these new use cases require a different type of computational horsepower to fuel their advanced capabilities. Bringing the GPU into the data center environment helps meet rising requirements for elevated computational demands and always-growing mountains of data.

Today, GPUs are widely used in both on-premises and cloud data center environments and are often virtualized in order to enable more flexibility and efficiency. Intel is dedicated to stewarding the evolution of GPU technology as it becomes a mainstay in the modern data center. Our currently available Intel® Flex Series GPU offerings and Intel® Data Center GPU Max Series provide optimized solutions for augmenting your data center’s capabilities with powerful and efficient GPU performance.

These data center offerings represent a core part of the Intel® GPU mission: bringing a balance of price and performance to the GPU market and providing data center professionals with more choices to support advanced, innovation-enabling use cases.

Data Center GPUs vs. CPUs

GPUs are deployed in the data center to augment CPU capabilities with additional computing horsepower.

While both CPUs and GPUs are silicon-based microprocessors and handle data, they’re built for different tasks. CPUs are suited to a wide number of workloads and applications, especially those where latency or per-core performance are critical concerns. They focus a smaller number of cores on quickly accomplishing individual tasks. This makes CPUs well suited for jobs such as handling databases and executing serial computing tasks.

That’s where GPUs come in. GPUs began as specialized ASICs, developed to accelerate specific 3D rendering tasks. Over time, these fixed-function engines became more programmable and more flexible. Consumers commonly use GPUs for gaming. However, in the data center, GPUs have evolved to become more general purpose parallel processors, handling a growing range of applications and supporting demanding use cases. While CPUs offer a small number of cores, GPUs offer thousands, allowing them to better support parallel operations.

Why Use GPUs in the Data Center?

If your organization is exploring advanced use cases such as AI, analytics, simulations, or modeling, GPUs can be a vital component in allowing your specialists to carry out their tasks quickly and effectively. They can also be crucial to enabling cloud gaming offerings.

GPUs unlock workload acceleration to help jobs finish faster and allow users to get more done. Without a high-performance GPU, many of today’s technologies and applications can face overly long load times, encounter performance issues, or simply not function.

Data Center GPU Use Cases

GPUs can be essential for many of today’s most powerful technologies.

For AI, deep learning, and machine learning, GPUs help train, optimize, and operate complex algorithms that enable machines to do amazing things. For deep learning training with several neural network layers or on massive sets of certain data, like 2D images, a GPU or other accelerators are ideal. Deep learning algorithms have been adapted to use a GPU-accelerated approach, gaining a significant boost in performance and bringing training times to a feasible and viable range for many real-world problems.

Data center GPUs are also used to enable advanced 3D rendering capabilities for gaming, media production, AR/VR, and other cutting-edge content. Cloud gaming is a rapidly emerging use case for data center GPUs. Used in a virtualized data center environment, data center GPUs provide high performance along with flexibility and efficiency—enabling remote or mobile employees to carry out their most complex and demanding work from anywhere.

Likewise, analytics, simulation, and modeling workloads all benefit from data center GPUs. Because these applications rely on large sets of complex data, the capabilities of the GPU help to speed processing times and allow for more-in-depth and wide-ranging analysis.

Implementing GPUs in the Data Center

Bringing GPUs into your data center environment is not without challenges. These high-performance tools demand more energy and space. They also create dramatically higher heat levels as they operate. These factors impact your data center infrastructure and can raise power costs or create reliability problems. Addressing power and cooling concerns with the right infrastructure is essential to a successful data center GPU implementation. Be sure to assess your rack power distribution units (PDUs), uninterruptible power supplies, and cooling capacity as you deploy GPUs in your environment. Insufficient power can lead to performance and availability issues. Likewise, inadequate cooling capacity can lead to downtime or damaged equipment.

In virtualized environments, a data center GPU can be used to augment multiple CPUs. Taking advantage of this can help you maximize your spend and optimize resource use. But keep in mind that virtualized GPUs can also introduce additional licensing requirements.

Intel Data Center GPU Offerings

As you seek to enable next-gen use cases, Intel has both current and future data center GPU offerings that can help you realize the right balance of price and performance in your environment.

Currently, we offer the Intel® Data Center GPU Flex Series, providing flexible, robust, and open GPU solutions. This series supports a diverse range of workloads, including media streaming and cloud gaming, AI visual inference, and virtual desktop infrastructure workloads. The Intel® Data Center GPU Flex Series supports an open, standards-based software stack optimized for density and quality with critical server capabilities for high reliability, availability, and scalability. This helps reduce the need for data centers to use disparate solutions and manage heterogenous or proprietary environments.

Our upcoming data center GPU offering will bring new levels of performance and efficiency to the high performance computing space.

Additionally, Intel offers software tools that can help accelerate and simplify the development of advanced applications that leverage GPUs in the data center. Our Intel® oneAPI toolkits for use cases such as rendering, analytics, HPC, and IoT enable cross-architecture programming that simplifies the process of building advanced applications that can run seamlessly across CPUs, GPUs, and other accelerators. We’re also working alongside open source communities such as PyTorch and TensorFlow to enable upstream optimizations for GPU-centric workloads.

Unlock Innovation with Data Center GPUs

The ongoing evolution of today’s technologies means that data center GPUs will play an increasingly critical role in your data center environment going forward.

Intel is dedicated to fostering the continued evolution of GPUs, with a strong focus on innovative products and deep collaboration with our ecosystem and open source partners. As you seek to augment your data center capabilities with GPUs and maximize the power of AI, analytics, 3D rendering, and other innovative applications, we’re ready to help.

Source: Intel
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