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Avispado is a 64-bit in-order RISC-V processor core engineered for efficiency and versatility within energy-conscious systems. This core supports a 2-wide in-order pipeline, which allows for streamlined instruction decoding and execution. Its compact design fits well in SOCs aimed at machine learning markets where power and space efficiency are crucial yet it retains the capacity to handle demanding processing tasks. With the inclusion of Gazzillion Misses™ technology, Avispado can handle high sparseness in data effectively, particularly beneficial in machine learning workloads. The core's full compatibility with RISC-V vector specifications and open vector interfaces offers flexibility in deploying various vector solutions, reducing the energy demanded by operations. Avispado is multiprocessor-ready and supports cache-coherent environments, ensuring it can be scaled as operations demand, from minimal cores up to comprehensive systems. It is suitable for applications looking to leverage high throughput with minimized silicon investments, making it a favorable choice for efficiently deploying machine learning and recommendation system support.
The Atrevido is a customizable 64-bit RISC-V processor core that showcases standout performance with its out-of-order execution engine. This core is adept at handling memory-intensive applications due to its extensive support for unaligned memory accesses and robust memory management features, making it Linux-ready right out of the gate. Designed for high-bandwidth scenarios, Atrevido excels particularly in machine learning and AI workloads, configurable in 2/3/4-wide out-of-order settings for optimal versatility. Equipped with features such as register renaming and vector processing capabilities, Atrevido is tailored for high-performance applications. It supports the RISC-V vector specification and can seamlessly integrate with custom vector units, offering comprehensive vector processing functionality. Gazzillion Misses™ technology enhances this core's abilities, allowing it to manage sparse data and recommend system operations efficiently. Targeted at diverse markets including machine learning and high-performance computing (HPC), Atrevido is optimized for handling sparse data, typical in applications such as sparse matrices, recommendation systems, and key-value stores. The core's overarching design philosophy emphasizes maximizing data throughput while minimizing the silicon footprint, making it a fit choice for both embedded and data center-level applications.
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