Technology
Pioneering the Next Generation of Edge AI Hardware
Discover the breakthroughs powering ultra-efficient, high-performance machine learning at the edge.
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Core Innovations
Revolutionary Hardware Architecture
Our hardware accelerators redefine what’s possible in edge AI by combining advanced memristor technology, a RISC-V processing core, and a custom 5-bit computation framework. These innovations allow for unparalleled energy efficiency, reduced latency, and scalability.
Memristor-Based Storage: Memristors provide non-volatile memory with zero-power retention, ideal for storing neural network weights in a low-energy state. This setup drastically reduces the need for constant data refreshes, leading to significant power savings.
Custom 5-Bit Computation Framework: Unlike traditional 16-bit or 32-bit systems, our unique 5-bit encoding compresses data without sacrificing model accuracy, enabling faster computations and lower power consumption.
Hybrid Analog-Digital Design: By integrating analog in-memory computing with digital processing, we achieve both computational density and precision. This design enables rapid parallel processing, mirroring the efficiency of biological neural systems.
Key Features
Optimized Data Flow with Explicit De-coupled Data Orchestration (EDDO)
Our Explicit De-coupled Data Orchestration (EDDO) mechanism ensures that data flows seamlessly throughout the system, reducing bottlenecks and eliminating unnecessary data movement. This improves overall system throughput and minimizes latency, which is essential for applications requiring real-time processing.
Fused Data Flow Mechanism
Our hardware architecture incorporates a fused data flow, eliminating redundant operations and optimizing data movement. By co-locating memory and processing, our accelerator can handle larger AI models with minimal power requirements, ideal for edge devices.
Software-Friendly Integration
Our hardware is designed for effortless integration with major machine learning frameworks like PyTorch. By adding a single line of code, developers can deploy their ML models on our accelerator, making it easy to transition from model development to high-performance inference on edge devices.
Technical Benefits
Energy Efficiency
By combining analog in-memory computing with advanced memristor technology, our hardware minimizes energy usage to unprecedented levels. Testing reveals energy savings of up to 80% compared to traditional digital-only solutions, making our hardware ideal for IoT and other low-power applications.
Low Latency for Real-Time Applications
Our design eliminates the need for external memory, significantly reducing data transfer times. The resulting reduction in latency makes our accelerators well-suited for applications requiring real-time processing, such as autonomous driving, industrial automation, and smart city technologies.
Scalability and Adaptability
Our hardware’s custom number system and modular design allow for easy adaptability to evolving AI models. This flexibility supports the integration of new models and technologies without extensive re-engineering, ensuring that our accelerator remains a long-term solution for edge AI applications.
Technology in Action
Real-World Applications
Our technology empowers a wide range of applications where high performance and low power consumption are crucial.
IoT Devices: Smart sensors and IoT devices can run complex ML models on-device, minimizing cloud dependence and extending battery life.
Autonomous Vehicles: Inference capabilities at the edge provide real-time decision-making essential for safety and performance.
Healthcare Devices: Portable diagnostic tools can process patient data locally, ensuring faster insights while maintaining privacy.
Case Studies
Our hardware has demonstrated up to 250x energy efficiency improvements for large models like BERT and CNN, making high-performance edge AI practical and scalable.
Ready to Learn More?
Get in touch with us to discuss how our technology can transform your AI applications at the edge. Whether you're an innovator, developer, or industry leader, we’re here to help you unlock the full potential of edge computing.
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