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Specially designed for accelerating AI recommendation systems, the RecAccel N3000 PCIe card offers exceptional performance in handling data-intensive AI workloads. It stands out due to its advanced architecture, which allows for high efficiency and fast processing speeds in recommendation tasks. The PCIe card is optimized to interact with existing infrastructures, providing a straightforward solution for enterprises looking to enhance their AI capabilities without significant investments in new hardware. This product excels in performance metrics, offering up to a million DLRM inferences per Joule, which makes it highly power-efficient and cost-effective. Moreover, the RecAccel N3000 PCIe ensures compatibility with prevailing AI frameworks, thus allowing users to upgrade their systems seamlessly. This compatibility, combined with power efficiency and high performance, makes it a preferred choice for businesses that require reliable AI recommendations capabilities.
The Evo Gen 5 PCIe Card is specifically crafted for AI inferencing tasks, aiming to enhance performance while optimizing power consumption. This card is a formidable tool in enabling enterprises to address the growing demand for AI inference capabilities, leveraging the Gen 5 architecture to deliver unparalleled speeds in processing AI tasks. Designed with flexibility in mind, the Evo Gen 5 easily slots into existing IT infrastructures, ensuring minimal disruption while significantly boosting computing capabilities. With its advanced architecture, it supports complex AI workloads, allowing businesses to explore AI applications with greater confidence and capability. The Evo Gen 5 PCIe Card is particularly beneficial for industries looking to handle large volumes of data swiftly and accurately, facilitating real-time AI analysis and boosting productivity through improved inference rates. Its efficient design ensures that energy costs are kept low, making it a cost-effective addition to any AI-driven enterprise.
The RecAccel AI Platform is a cutting-edge computing solution tailored for high-accuracy AI applications. Engineered for environments that desperately require precision and speed, this platform stands out with its ability to handle complex AI tasks with remarkable efficiency. Its architecture is calibrated to support seamless integration, ensuring that enterprises can adopt AI solutions without facing significant system overhauls. This platform is equipped to maintain crucial accuracy levels across intensive workloads, making it indispensable in fields where precision cannot be compromised. By harnessing significant computational power with energy-saving capabilities, the RecAccel AI Platform helps businesses minimize costs while maximizing performance. This blend of power efficiency and high-performance computing positions the RecAccel AI Platform as a desirable choice for organizations aiming to harness the full potential of AI technology.
The Raptor N3000 is a pioneering AI accelerator designed specifically to handle demanding tasks in AI inferencing. Built with an eye towards efficiency, the Raptor N3000 provides an optimized solution for data centers seeking to enhance their recommendation system capabilities. Its design enables processing speeds capable of handling up to a million DLRM inferences per Joule—positioning it as a leader in power efficiency. With its architecture, the Raptor N3000 supports a wide range of applications, from basic AI tasks to more complex deep learning scenarios. This chip's robust performance in emulation has proven it to be a unique market offer, meeting high standards in both speed and accuracy. The Raptor N3000 is optimized to maintain INT8 DLRM models with a precision level nearing FP32, which is a testament to its precision and usability in high-stake environments. A key feature of the Raptor N3000 is its ability to integrate seamlessly with existing systems, providing a plug-and-play solution that doesn't disrupt current infrastructures. Its reliability and scalable nature make it an attractive choice for enterprises looking to leverage AI without the costs and risks of overhauling their existing setups.
The RecAccel N3000 represents a significant leap in AI inference technology, emphasizing the importance of tailored design to meet specific workload requirements. Engineered for high-density environments, this AI accelerator focuses on accelerating recommendation workloads, utilizing novel techniques to push the boundaries of what's possible in AI processing. In a market where power efficiency and performance are often at odds, the RecAccel N3000 strikes a balance by achieving superior energy performance metrics. The chip is designed to deliver top-tier recommendation accuracy, with testing indicating its ability to support one million inferences per Joule. This efficiency not only reduces operational costs but also contributes to a more sustainable technology strategy. Beyond raw performance metrics, the RecAccel N3000 shines in its compatibility with popular AI frameworks, which allows users to integrate it seamlessly into existing infrastructures. This adaptability, combined with proven accuracy levels that hover close to 99.97% of FP32, makes it an invaluable tool for businesses looking to gain competitive advantage through enhanced AI capabilities.
The Viper Series Gen AI PCIe Card is designed to integrate seamlessly into existing systems, transforming them into powerful AI computation hubs. Known for its robustness and versatility, this card is ideal for enterprises aiming to scale up AI capabilities without the complexities of building new systems from scratch. Engineered to support high-throughput AI tasks, the Viper Series combines the efficient use of AI hardware with user-friendly software tools. Its plug-and-play functionality allows enterprises to quickly deploy AI solutions and accelerate computing tasks, enhancing overall performance metrics and operational efficiency. The Viper Series is particularly noted for its adaptability in various AI applications, from enterprise-level solutions to more specific industrial applications. By reducing CPU loads and offloading intensive computes processes, it ensures smoother operation and energy-efficient performance in demanding computational environments.
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