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EdgeThought represents Skymizer's commitment to bringing large language model (LLM) capabilities to edge devices through its compiler-centric approach. Built for on-device inference, this IP is engineered to offer cost-efficient AI solutions without compromising on performance. The design uses a software-hardware co-design strategy that minimizes the hardware footprint while maximizing performance. This resource-efficient architecture allows for effective execution of complex LLM inference tasks on devices with limited resources. EdgeThought's dynamic decompression engine reduces the storage and bandwidth needs while preserving model accuracy, making it ideal for scalable deployment in diverse environments. A key aspect of EdgeThought is its integration capabilities, which allow it to work seamlessly with popular AI frameworks and APIs. By supporting a broad range of toolkits for model fine-tuning, EdgeThought ensures robust and reliable performance across a variety of use cases, from IoT devices to high-performance edge servers.
HyperThought is Skymizer's next-generation Local Processing Unit (LPU) designed specifically for large language models (LLMs). This IP is engineered for optimal performance and power efficiency, enabling real-time interactive AI with a focus on multimodal capabilities. HyperThought employs advanced compression techniques to minimize the size of language models, which helps in reducing parameter counts and DRAM bandwidth requirements. Its balanced performance allows for impressive compute efficiency, achieving high throughput levels with minimal hardware resources. Even with configurations that include octa-core designs, HyperThought can reach processing speeds up to 240 tokens/second for substantial model prefill tasks, such as those involving Llama2 7B. The robust architecture of HyperThought supports secure operations with LISA v3, ensuring that every interaction is protected. By integrating the LPU IP as the core processing engine, Skymizer's platform is set to revolutionize AI application efficiency and effectiveness.
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