Akamai Rolls Out Cloud Infrastructure and Services Powered by NVIDIA, Optimized for Video Processing
- Akamai's new media-optimized offering with NVIDIA GPUs significantly improves video processing speed and efficiency for media and entertainment companies.
- The NVIDIA RTX 4000 Ada Generation GPU processes frames per second 25x faster than traditional CPU-based methods, enhancing productivity and economics for companies.
- Akamai's solution allows companies to deploy scalable, resilient architectures with faster, more reliable workloads, supporting multicloud architectures and cloud agnostic environments.
- None.
Insights
The introduction of Akamai's GPU-based encoding service, leveraging NVIDIA's RTX 4000 GPUs, represents a potential pivot point for the media and entertainment industry's approach to video processing. It's essential to understand the industry's ongoing transition from CPU-based methods, which are more time and resource-intensive, to GPU-based solutions offering significant speed and efficiency improvements. This shift will likely lead to a restructuring of the competitive landscape, with companies that can integrate GPU-accelerated workflows potentially gaining an edge in both cost and performance.
For investors and stakeholders, it's relevant to evaluate Akamai's strategic move in terms of future market share acquisition. This is especially pertinent given that the media industry is increasingly reliant on high-quality, rapid video content delivery as consumer demands escalate. Akamai's benchmarking claims, if validated by independent testing, could strengthen its market position and provide grounds for investment consideration based on anticipated growth in demand for more efficient video processing technologies.
Akamai Technologies' foray into GPU-based cloud services for the media sector, backed by NVIDIA's hardware, has the potential to shift the revenue dynamics for the company. The emphasis on cost-effectiveness and performance could attract a significant clientele from the media and entertainment industry, looking to optimize video processing workflows. Historically, Akamai's financial performance has been closely tied to its ability to innovate and remain at the forefront of the cloud services market.
In terms of financials, a key aspect to watch will be the service adoption rate among existing and new customers. Revenue growth from this service line could impact earnings positively, while margins may see improvement due to the economies of scale that GPU processing can provide. Future earnings reports should be examined for specific mentions of the performance of the newly launched services to gauge their success and potential impact on Akamai's overall financial health.
The significance of Akamai's decision to base its new cloud service on NVIDIA GPUs extends beyond immediate market impact and reflects broader industry trends toward specialized, high-performance compute solutions. This development highlights the increasing importance of GPUs in cloud computing architectures, particularly for data- and processing-intensive tasks such as video encoding and machine learning applications.
From an industry perspective, Akamai's move may incentivize competitors to accelerate the adoption of similar technologies, potentially leading to increased demand for NVIDIA's GPUs and subsequent impacts on its supply chain and production strategy. As more companies opt for GPU-accelerated services, this could shape future R&D directions and partnerships within the technology sector, with implications for long-term technological innovation and market growth trajectories.
New encoding using cost-effective NVIDIA GPUs enables optimal processing for media companies
Internal benchmarking conducted by Akamai demonstrated that GPU-based encoding using the NVIDIA RTX 4000 processes frames per second (FPS) 25x faster than traditional CPU-based encoding and transcoding methods, which presents a significant advancement in the way streaming service providers address their typical workload challenges.
Using Akamai's offering, media and entertainment companies can build scalable, resilient architectures and deploy workloads that will be faster, more reliable, and portable, while taking advantage of the world's most distributed cloud platform and integrated content delivery and security services.
"Media companies need low-latency, reliable compute resources that maintain the portability of the workloads they create," said Shawn Michels, Vice President of Cloud Products at Akamai. "NVIDIA GPUs provide superior price performance when deployed on Akamai's global edge platform. Together with our Qualified Compute Partners and open platform, we give our customers the capability to architect their next-gen workloads to be cloud agnostic and support multicloud architectures."
The need for industry optimized GPUs
In a market hyper-focused on using NVIDIA GPUs to support large language modeling, Akamai's media-tailored GPU service homes in on an industry underserved by current industry offerings, which can be expensive. Building on its rich heritage and deep experience in the space, Akamai fine-tuned its new GPU offering to meet the demanding and specific requirements of the media and entertainment industry.
Use cases
The NVIDIA RTX 4000 GPU achieves the speed and power efficiency necessary to tackle demanding creative, design, and engineering workflows for digital content creation, 3D modeling, rendering, inferencing, and video content and streaming. Media-specific use cases include:
- Video transcoding and live video streaming: GPUs can perform faster-than-real-time transcoding of live video streams, improving the streaming experience by reducing buffering and even playback, while GPU-based encoding improves efficiency and reduces processing times compared with traditional CPU-based transcoding. The NVIDIA RTX 4000 GPU is equipped with the latest-generation NVIDIA NVENC and NVDEC hardware, which enables additional capacity for simultaneous encoding and decoding tasks. This is critical for applications requiring high-throughput video processing, such as live streaming. The eighth-generation NVENC engines provide support for the latest video codecs, including the highly efficient AV1 codec, which enables higher-quality video at lower bitrates.
- Virtual reality (VR) and augmented reality (AR) content: VR and AR applications require the rendering of 3D graphics and multimedia content in real time. GPUs are ideal for processing such content.
While Akamai optimized the new solution for the media market, the new offering also has applicability for developers and companies looking to build apps tied to several other industry use cases, including:
- Generative artificial intelligence and machine learning (Gen AI/ML): One of the primary applications of GPU cloud computing is in generative AI/ML. GPUs are well-suited for tasks such as training and inference with neural networks, as they can perform many calculations in parallel, which allows faster and more efficient training of new models, which can lead to better accuracy and performance. The NVIDIA RTX 4000 GPU harnesses the NVIDIA Ada Lovelace architecture to deliver exceptional performance in inferencing tasks. A total of 192 fourth-generation Tensor Cores accelerate more data types and include a new Fine-Grained Structured Sparsity feature for up to 4x the throughput for tensor matrix operations when compared with the previous generation. The inclusion of 20 GB of GDDR6 memory provides extensive capacity for large models and datasets.
- Data analysis and scientific computing: GPU cloud computing is also commonly used in data analysis and scientific computing because of the nature of its tasks, which often involve processing large amounts of data. These tasks are time-consuming and computationally intensive. GPUs can help accelerate these tasks by processing large amounts of data in parallel, which enables faster and more efficient analysis and simulation.
- Gaming and graphics rendering: GPUs are widely used in the gaming industry, mainly for graphics rendering and other tasks related to video game development. This is because GPUs are designed to handle complex graphics processing and can provide fast, high-quality rendering of 3D graphics.
- High-performance computing: GPU-enabled cloud computing is commonly used for high-performance computing applications, such as modeling and simulation, that require fast and efficient processing of large amounts of data. GPUs can also be used to accelerate simulations, calculations, and other computationally intensive tasks, which leads to faster results and better performance.
"In order to support a wide range of workloads, you need a wide array of compute instances," continued Michels. "What we're doing with industry-optimized GPUs is one of many steps we're taking for our customers to increase instance diversity across the entire continuum of compute to drive and power edge native applications."
Akamai at the 2024 NAB Show
Akamai will show its range of cloud-based media delivery solutions at the 2024 NAB Show in the Akamai Lounge (meeting space W235LMR, Level 2) April 14–17, in
Akamai is also hosting a Lunch & Learn session during which partners Ateme, Hydrolix, and Yospace will share how they are building next-generation media workflows on the Akamai distributed cloud computing platform. The event takes place Tuesday, April 16, from 11 AM–12:30 PM PT, in the Akamai Lounge. Visit the registration page for more information and to reserve a space.
About Akamai
Akamai powers and protects life online. Leading companies worldwide choose Akamai to build, deliver, and secure their digital experiences — helping billions of people live, work, and play every day. Akamai Connected Cloud, a massively distributed edge and cloud platform, puts apps and experiences closer to users and keeps threats farther away. Learn more about Akamai's cloud computing, security, and content delivery solutions at akamai.com and akamai.com/blog, or follow Akamai Technologies on X, formerly known as Twitter, and LinkedIn.
Chris Nicholson
Akamai Media Relations
+1.508.517.3703
cnichols@akamai.com
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FAQ
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