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The Wormhole processor series offers robust solutions for balancing power and computational throughput efficiency, specifically geared toward AI applications. This series includes the n150s and n300s models, designed with differing capacities to serve varying demands of AI computing. The n150s, with its standard size and 3/4 length, incorporates a single Wormhole processor and is optimized for applications that require up to 160 watts. This design makes it perfect for scalable AI solutions that do not compromise on performance, ensuring efficient processing power for complex AI models. The n300s elevates the capabilities further by featuring dual Wormhole processors, doubling the computational power, and is designed to operate at up to 300 watts. This model is particularly suitable for high-output environments such as data centers or for users requiring intensive AI model computations. With its standard height and substantial power envelope, the n300s provides a comprehensive solution for large-scale AI operations. The Wormhole family is built for AI environments demanding high computational power and efficiency, delivering peak performance without excessive power draw, ideally suited for cutting-edge AI developments and inferences in demanding scenarios.
Grayskull is a state-of-the-art AI Graph Processor designed for optimized artificial intelligence computation. It comes in two variations catering to different performance needs: the e75 and the e150. The e75 is a compact, low-profile PCIe Gen 4 board, equipped with a single Grayskull processor. This entry-level board is ideal for applications requiring moderate power, operating at 75 watts, making it suitable for personal use or scaling small AI projects. The card is half-length, allowing for easy integration into smaller systems. On the other hand, the e150 variant is engineered for higher demands. It is a standard height board, extending to three-quarters in length, ensuring it can manage more significant workloads. This version also includes a Grayskull processors, pushing the boundaries of power efficiency by operating at up to 200 watts. This increased power cap allows for greater throughput, making it more suitable for intensive AI computations in either professional or research settings. Grayskull processors are fundamentally designed to maximize the use of SRAM for its self-attention layers, optimizing speed and reducing latency compared to traditional DRAM implementations. This technique ensures rapid data processing, necessary for sophisticated AI models, supporting diverse AI applications and research projects.
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