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Forget CPUs! RaiderChip Has a Hardware-Based Generative AI Accelerator

The Spanish startup is pushing the limits of edge AI with a new accelerator reportedly trumping competitors in efficiency and token generation speed.

allaboutcircuits.com, Feb. 01, 2025 – 

Spanish AI startup RaiderChip recently announced its new GenAI NPU, a fully hardware-based accelerator designed to optimize generative AI inference at the edge. Unlike hybrid solutions that rely on software execution, the GenAI NPU integrates all large language model (LLM) operations into hardware to eliminate processing latency and deliver deterministic, real-time performance. The company's website lacks much in the way of engineering-level technical details about the NPU, but it does offer information about its performance and features.

GenAI NPU: Processing Complex LLMs at the Edge

RaiderChip's GenAI NPU is a fully hardware-based accelerator designed to optimize generative AI inference at the edge. According to the company, this architecture eliminates the need for external processors by embedding all LLM operations within the hardware itself. While hybrid solutions tend to rely on software execution, the GenAI NPU reportedly achieves a 2.4× increase in token generation speed per available memory bandwidth by removing hardware-software communication latency.

The accelerator is also said to optimize memory efficiency by maximizing the number of tokens generated per gigabyte per second of available memory bandwidth. Unlike competing solutions that require high-bandwidth memory (HBM), the GenAI NPU achieves high performance using cost-effective DDR or LPDDR memory. This design reduces hardware cost, energy consumption, and overall system size without sacrificing computational power. Performance comparisons indicate a 37% efficiency gain over Intel's Gaudi 2, a 28% improvement over Nvidia's cloud GPUs, and a 25% advantage over Google's TPU v5e.

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