All IPs > Processor > AI Processor
The AI Processor category within our semiconductor IP catalog is dedicated to state-of-the-art technologies that empower artificial intelligence applications across various industries. AI processors are specialized computing engines designed to accelerate machine learning tasks and perform complex algorithms efficiently. This category includes a diverse collection of semiconductor IPs that are built to enhance both performance and power efficiency in AI-driven devices.
AI processors play a critical role in the emerging world of AI and machine learning, where fast processing of vast datasets is crucial. These processors can be found in a range of applications from consumer electronics like smartphones and smart home devices to advanced robotics and autonomous vehicles. By facilitating rapid computations necessary for AI tasks such as neural network training and inference, these IP cores enable smarter, more responsive, and capable systems.
In this category, developers and designers will find semiconductor IPs that provide various levels of processing power and architectural designs to suit different AI applications, including neural processing units (NPUs), tensor processing units (TPUs), and other AI accelerators. The availability of such highly specialized IPs ensures that developers can integrate AI functionalities into their products swiftly and efficiently, reducing development time and costs.
As AI technology continues to evolve, the demand for robust and scalable AI processors increases. Our semiconductor IP offerings in this category are designed to meet the challenges of rapidly advancing AI technologies, ensuring that products are future-ready and equipped to handle the complexities of tomorrow’s intelligence-driven tasks. Explore this category to find cutting-edge solutions that drive innovation in artificial intelligence systems today.
BrainChip's Akida Neural Processor IP is a groundbreaking development in neuromorphic processing, designed to mimic the human brain in interpreting sensory inputs. By implementing an event-based architecture, it processes only the critical data at the point of acquisition, achieving unparalleled performance with significantly reduced power consumption. This architecture enables on-chip learning, reducing dependency on cloud processing, thus enhancing privacy and security.\n\nThe Akida Neural Processor IP supports incremental learning and high-speed inference across a vast range of applications, making it highly versatile. It is structured to handle data sparsity effectively, which cuts down on operations substantially, leading to considerable improvements in efficiency and responsiveness. The processor's scalability and compact design allow for wide deployment, from minimal-node setups for ultra-low power operations to more extensive configurations for handling complex tasks.\n\nImportantly, the Akida processor uses a fully customizable AI neural processor that leverages event-based processing and an on-chip mesh network for seamless communication. The technology also features support for hybrid quantized weights and provides robust tools for integration, including fully synthesizable RTL IP packages, hardware-based event processing, and on-chip learning capabilities.
The Akida 2nd Generation is an evolution of BrainChip's innovative neural processor technology. It builds upon its predecessor's strengths by delivering even greater efficiency and a broader range of applications. The processor maintains an event-based architecture that optimizes performance and power consumption, providing rapid response times suitable for edge AI applications that prioritize speed and privacy.\n\nThis next-generation processor enhances accuracy with support for 8-bit quantization, which allows for finer grained processing capabilities and more robust AI model implementations. Furthermore, it offers extensive scalability, supporting configurations from a few nodes for low-power needs to many nodes for handling more complex cognitive tasks. As with the previous version, its architecture is inherently cloud-independent, enabling inference and learning directly on the device.\n\nAkida 2nd Generation continues to push the boundaries of AI processing at the edge by offering enhanced processing capabilities, making it ideal for applications demanding high accuracy and efficiency, such as automotive safety systems, consumer electronics, and industrial monitoring.
MetaTF is BrainChip's proprietary software development framework built to streamline the creation, training, and deployment of neural networks on their Akida neuromorphic processor. This tool is designed specifically for working with edge AI, complementing the hardware capabilities of Akida by providing a rich environment for model development and conversion.\n\nThe framework supports the conversion of traditional TensorFlow and Keras models into spiking neural networks optimized for BrainChip's unique event-based processing. This conversion allows developers to harness the energy efficiency and performance benefits of the Akida architecture without needing to overhaul existing machine learning frameworks.\n\nMetaTF facilitates the adaptation of models to the Akida system through its model zoo, which includes various pre-configured network models, and offers comprehensive tools for simulation and testing. This environment makes it an indispensable resource for businesses aiming to deploy sophisticated AI applications at the edge, minimizing development time while maximizing performance and efficiency.
The KL730 is a sophisticated AI System on Chip (SoC) that embodies Kneron's third-generation reconfigurable NPU architecture. This SoC delivers a substantial 8 TOPS of computing power, designed to efficiently handle CNN network architectures and transformer applications. Its innovative NPU architecture significantly optimizes DDR bandwidth, providing powerful video processing capabilities, including supporting 4K resolution at 60 FPS. Furthermore, the KL730 demonstrates formidable performance in noise reduction and low-light imaging, positioning it as a versatile solution for intelligent security, video conferencing, and autonomous applications.
The Metis AIPU PCIe AI Accelerator Card offers exceptional performance for AI workloads demanding significant computational capacity. It is powered by a single Metis AIPU and delivers up to 214 TOPS, catering to high-demand applications such as computer vision and real-time image processing. This PCIe card is integrated with the Voyager SDK, providing developers with a powerful yet user-friendly software environment for deploying complex AI applications seamlessly. Designed for efficiency, this accelerator card stands out by providing cutting-edge performance without the excessive power requirements typical of data center equipment. It achieves remarkable speed and accuracy, making it an ideal solution for tasks requiring fast data processing and inference speeds. The PCIe card supports a wide range of AI application scenarios, from enhancing existing infrastructure capabilities to integrating with new, dynamic systems. Its utility in various industrial settings is bolstered by its compatibility with the suite of state-of-the-art neural networks provided in the Axelera AI ecosystem.
The Yitian 710 Processor is an advanced Arm-based server chip developed by T-Head, designed to meet the extensive demands of modern data centers and enterprise applications. This processor boasts 128 high-performance Armv9 CPU cores, each coupled with robust caches, ensuring superior processing speeds and efficiency. With a 2.5D packaging technology, the Yitian 710 integrates multiple dies into a single unit, facilitating enhanced computational capability and energy efficiency. One of the key features of the Yitian 710 is its memory subsystem, which supports up to 8 channels of DDR5 memory, achieving a peak bandwidth of 281 GB/s. This configuration guarantees rapid data access and processing, crucial for high-throughput computing environments. Additionally, the processor is equipped with 96 PCIe 5.0 lanes, offering a dual-direction bandwidth of 768 GB/s, enabling seamless connectivity with peripheral devices and boosting system performance overall. The Yitian 710 Processor is meticulously crafted for applications in cloud services, big data analytics, and AI inference, providing organizations with a robust platform for their computing needs. By combining high core count, extensive memory support, and advanced I/O capabilities, the Yitian 710 stands as a cornerstone for deploying powerful, scalable, and energy-efficient data processing solutions.
The Metis AIPU M.2 Accelerator Module is designed for edge AI applications that demand high-performance inference capabilities. This module integrates a single Metis AI Processing Unit (AIPU), providing an excellent solution for AI acceleration within constrained devices. Its capability to handle high-speed data processing with limited power consumption makes it an optimal choice for applications requiring efficiency and precision. With 1GB of dedicated DRAM memory, it seamlessly supports a wide array of AI pipelines, ensuring rapid integration and deployment. The design of the Metis AIPU M.2 module is centered around maximizing performance without excessive energy consumption, making it suitable for diverse applications such as real-time video analytics and multi-camera processing. Its compact form factor eases incorporation into various devices, delivering robust performance for AI tasks without the heat or power trade-offs typically associated with such systems. Engineered to problem-solve current AI demands efficiently, the M.2 module comes supported by the Voyager SDK, which simplifies the integration process. This comprehensive software suite empowers developers to build and optimize AI models directly on the Metis platform, facilitating a significant reduction in time-to-market for innovative solutions.
The NMP-750 is a high-performance accelerator designed for edge computing, particularly suited for automotive, AR/VR, and telecommunications sectors. It boasts an impressive capacity of up to 16 TOPS and 16 MB local memory, powered by a RISC-V or Arm Cortex-R/A 32-bit CPU. The three AXI4 interfaces ensure seamless data transfer and processing. This advanced accelerator supports multifaceted applications such as mobility control, building automation, and multi-camera processing. It's designed to cope with the rigorous demands of modern digital and autonomous systems, offering substantial processing power and efficiency for intensive computational tasks. The NMP-750's ability to integrate into smart systems and manage spectral efficiency makes it crucial for communications and smart infrastructure management. It helps streamline operations, maintain effective energy management, and facilitate sophisticated AI-driven automation, ensuring that even the most complex data flows are handled efficiently.
Designed for extreme low-power environments, the Tianqiao-70 RISC-V CPU core emphasizes energy efficiency while maintaining sufficient computational strength for commercial applications. It serves scenarios where low power consumption is critical, such as mobile devices, desktop applications, AI, and autonomous systems. This model caters to the requirements of energy-conscious markets, facilitating operations that demand efficiency and performance within minimal power budgets.
RaiderChip's GenAI v1 is a pioneering hardware-based generative AI accelerator, designed to perform local inference at the Edge. This technology integrates optimally with on-premises servers and embedded devices, offering substantial benefits in privacy, performance, and energy efficiency over traditional hybrid AI solutions. The design of the GenAI v1 NPU streamlines the process of executing large language models by embedding them directly onto the hardware, eliminating the need for external components like CPUs or internet connections. With its ability to support complex models such as the Llama 3.2 with 4-bit quantization on LPDDR4 memory, the GenAI v1 achieves unprecedented efficiency in AI token processing, coupled with energy savings and reduced latency. What sets GenAI v1 apart is its scalability and cost-effectiveness, significantly outperforming competitive solutions such as Intel Gaudi 2, Nvidia's cloud GPUs, and Google's cloud TPUs in terms of memory efficiency. This solution maximizes the number of tokens generated per unit of memory bandwidth, thus addressing one of the primary limitations in generative AI workflow. Furthermore, the adept memory usage of GenAI v1 reduces the dependency on costly memory types like HBM, opening the door to more affordable alternatives without diminishing processing capabilities. With a target-agnostic approach, RaiderChip ensures the GenAI v1 can be adapted to various FPGAs and ASICs, offering configuration flexibility that allows users to balance performance with hardware costs. Its compatibility with a wide range of transformers-based models, including proprietary modifications, ensures GenAI v1's robust placement across sectors requiring high-speed processing, like finance, medical diagnostics, and autonomous systems. RaiderChip's innovation with GenAI v1 focuses on supporting both vanilla and quantized AI models, ensuring high computation speeds necessary for real-time applications without compromising accuracy. This capability underpins their strategic vision of enabling versatile and sustainable AI solutions across industries. By prioritizing integration ease and operational independence, RaiderChip provides a tangible edge in applying generative AI effectively and widely.
Ventana's Veyron V2 CPU represents the pinnacle of high-performance AI and data center-class RISC-V processors. Engineered to deliver world-class performance, it supports extensive data center workloads, offering superior computational power and efficiency. The V2 model is particularly focused on accelerating AI and ML tasks, ensuring compute-intensive applications run seamlessly. Its design makes it an ideal choice for hyperscale, cloud, and edge computing solutions where performance is non-negotiable. This CPU is instrumental for companies aiming to scale with the latest in server-class technology.
The Jotunn8 represents a leap in AI inference technology, delivering unmatched efficiency for modern data centers. This chip is engineered to manage AI model deployments with lightning-fast execution, at minimal cost and high scalability. It ensures optimal performance by balancing high throughput and low latency, while being extremely power-efficient, which significantly lowers operational costs and supports sustainable infrastructures. The Jotunn8 is designed to unlock the full capacity of AI investments by providing a high-performance platform that enhances the delivery and impact of AI models across applications. It is particularly suitable for real-time applications such as chatbots, fraud detection, and search engines, where ultra-low latency and very high throughput are critical. Power efficiency is a major emphasis of the Jotunn8, optimizing performance per watt to control energy as a substantial operational expense. Its architecture allows for flexible memory allocation ensuring seamless adaptability across varied applications, providing a robust foundation for scalable AI operations. This solution is aimed at enhancing business competitiveness by supporting large-scale model deployment and infrastructure optimization.
The Chimera GPNPU from Quadric is designed as a general-purpose neural processing unit intended to meet a broad range of demands in machine learning inference applications. It is engineered to perform both matrix and vector operations along with scalar code within a single execution pipeline, which offers significant flexibility and efficiency across various computational tasks. This product achieves up to 864 Tera Operations per Second (TOPs), making it suitable for intensive applications including automotive safety systems. Notably, the GPNPU simplifies system-on-chip (SoC) hardware integration by consolidating hardware functions into one processor core. This unification reduces complexity in system design tasks, enhances memory usage profiling, and optimizes power consumption when compared to systems involving multiple heterogeneous cores such as NPUs and DSPs. Additionally, its single-core setup enables developers to efficiently compile and execute diverse workloads, improving performance tuning and reducing development time. The architecture of the Chimera GPNPU supports state-of-the-art models with its Forward Programming Interface that facilitates easy adaptation to changes, allowing support for new network models and neural network operators. It’s an ideal solution for products requiring a mix of traditional digital signal processing and AI inference like radar and lidar signal processing, showcasing a rare blend of programming simplicity and long-term flexibility. This capability future-proofs devices, expanding their lifespan significantly in a rapidly evolving tech landscape.
Designed for entry-level server-class applications, the SCR9 is a 64-bit RISC-V processor core that comes equipped with cutting-edge features, such as an out-of-order superscalar pipeline, making it apt for processing-intensive environments. It supports both single and double-precision floating-point operations adhering to IEEE standards, which ensure precise computation results. This processor core is tailored for high-performance computing needs, with a focus on AI and ML, as well as conventional data processing tasks. It integrates an advanced interrupt system featuring APLIC configurations, enabling responsive operations even under heavy workloads. SCR9 supports up to 16 cores in a multi-cluster arrangement, each utilizing coherent multi-level caches to maintain rapid data processing and management. The comprehensive development package for SCR9 includes ready-to-deploy toolchains and simulators that expedite software development, particularly within Linux environments. The core is well-suited for deployment in entry-level server markets and data-intensive applications, with robust support for virtualization and heterogeneous architectures.
The KL520 was Kneron's first foray into AI SoCs, characterized by its small size and energy efficiency. This chip integrates a dual ARM Cortex M4 CPU architecture, which can function both as a host processor and as a supportive AI co-processor for diverse edge devices. Ideal for smart devices such as door locks and cameras, it is compatible with various 3D sensor technologies, offering a balance of compact design and high performance. As a result, this SoC has been adopted by multiple products in the smart home and security sectors.
The KL630 chip stands out with its pioneering NPU architecture, making it the industry's first to support Int4 precision alongside transformer networks. This unique capability enables it to achieve exceptional computational efficiency and low energy consumption, suitable for a wide variety of applications. The chip incorporates an ARM Cortex A5 CPU, providing robust support for all major AI frameworks and delivering superior ISP capabilities for handling low light conditions and HDR applications, making it ideal for security, automotive, and smart city uses.
The NMP-350 is a cutting-edge endpoint accelerator designed to optimize power usage and reduce costs. It is ideal for markets like automotive, AIoT/sensors, and smart appliances. Its applications span from driver authentication and predictive maintenance to health monitoring. With a capacity of up to 1 TOPS and 1 MB of local memory, it incorporates a RISC-V/Arm Cortex-M 32-bit CPU and supports three AXI4 interfaces. This makes the NMP-350 a versatile component for various industrial applications, ensuring efficient performance and integration. Developed as a low-power solution, the NMP-350 is pivotal for applications requiring efficient processing power without inflating energy consumption. It is crucial for mobile and battery-operated devices where every watt conserved adds to the operational longevity of the product. This product aligns with modern demands for eco-friendly and cost-effective technologies, supporting enhanced performance in compact electronic devices. Technical specifications further define its role in the industry, exemplifying how it brings robust and scalable solutions to its users. Its adaptability across different applications, coupled with its cost-efficiency, makes it an indispensable tool for developers working on next-gen AI solutions. The NMP-350 is instrumental for developers looking to seamlessly incorporate AI capabilities into their designs without compromising on economy or efficiency.
The Polar ID Biometric Security System by Metalenz revolutionizes smartphone biometric security with its advanced imaging capabilities that capture the full polarization state of light. This system detects unique facial polarization signatures, enabling high-precision face authentication that even sophisticated 3D masks cannot deceive. Unlike traditional systems requiring multiple optical modules, Polar ID achieves secure recognition with a single image, ideal for secure digital payments and more. Operating efficiently across various lighting conditions, from bright daylight to complete darkness, Polar ID ensures robust security without compromising user convenience. By leveraging meta-optic technology, it offers a compact, cost-effective alternative to structured light solutions, suitable for widespread deployment across millions of mobile devices.
EW6181 is an IP solution crafted for applications demanding extensive integration levels, offering flexibility by being licensable in various forms such as RTL, gate-level netlist, or GDS. Its design methodology focuses on delivering the lowest possible power consumption within the smallest footprint. The EW6181 effectively extends battery life for tags and modules due to its efficient component count and optimized Bill of Materials (BoM). Additionally, it is backed by robust firmware ensuring highly accurate and reliable location tracking while offering support and upgrades. The IP is particularly suitable for challenging application environments where precision and power efficiency are paramount, making it adaptable across different technology nodes given the availability of its RF frontend.
The NMP-550 is tailored for enhanced performance efficiency, serving sectors like automotive, mobile, AR/VR, drones, and robotics. It supports applications such as driver monitoring, image/video analytics, and security surveillance. With a capacity of up to 6 TOPS and 6 MB local memory, this accelerator leverages either a RISC-V or Arm Cortex-M/A 32-bit CPU. Its three AXI4 interface support ensures robust interconnections and data flow. This performance boost makes the NMP-550 exceptionally suited for devices requiring high-frequency AI computations. Typical use cases include industrial surveillance and smart robotics, where precise and fast data analysis is critical. The NMP-550 offers a blend of high computational power and energy efficiency, facilitating complex AI tasks like video super-resolution and fleet management. Its architecture supports modern digital ecosystems, paving the way for new digital experiences through reliable and efficient data processing capabilities. By addressing the needs of modern AI workloads, the NMP-550 stands as a significant upgrade for those needing robust processing power in compact form factors.
The Dynamic Neural Accelerator II (DNA-II) is a highly efficient and versatile IP specifically engineered for optimizing AI workloads at the edge. Its unique architecture allows runtime reconfiguration of interconnects among computing units, which facilitates improved parallel processing and efficiency. DNA-II supports a broad array of networks, including convolutional and transformer networks, making it an ideal choice for numerous edge applications. Its design emphasizes low power consumption while maintaining high computational performance. By utilizing a dynamic data path architecture, DNA-II sets a new benchmark for IP cores aimed at enhancing AI processing capabilities.
xcore.ai is a powerful platform tailored for the intelligent IoT market, offering unmatched flexibility and performance. It boasts a unique multi-threaded micro-architecture that provides low-latency and deterministic performance, perfect for smart applications. Each xcore.ai contains 16 logical cores distributed across two multi-threaded processor tiles, each equipped with 512kB of SRAM and capable of both integer and floating-point operations. The integrated interprocessor communication allows high-speed data exchange, ensuring ultimate scalability across multiple xcore.ai SoCs within a unified development environment.
The RISC-V Core-hub Generators from InCore are tailored for developers who need advanced control over their core architectures. This innovative tool enables users to configure core-hubs precisely at the instruction set and microarchitecture levels, allowing for optimized design and functionality. The platform supports diverse industry applications by facilitating the seamless creation of scalable and customizable RISC-V cores. With the RISC-V Core-hub Generators, InCore empowers users to craft their own processor solutions from the ground up. This flexibility is pivotal for businesses looking to capitalize on the burgeoning RISC-V ecosystem, providing a pathway to innovation with reduced risk and cost. Incorporating feedback from leading industry partners, these generators are designed to lower verification costs while accelerating time-to-market for new designs. Users benefit from InCore's robust support infrastructure and a commitment to simplifying complex chip design processes. This product is particularly beneficial for organizations aiming to integrate RISC-V technology efficiently into their existing systems, ensuring compatibility and enhancing functionality through intelligent automation and state-of-the-art tools.
The KL530 is built with an advanced heterogeneous AI chip architecture, designed to enhance computing efficiency while reducing power usage. Notably, it is recognized as the first in the market to support INT4 precision and transformers for commercial applications. The chip, featuring a low-power ARM Cortex M4 CPU, delivers impressive performance with 1 TOPS@INT 4 computing power, providing up to 70% higher processing efficiency compared to INT8 architectures. Its integrated smart ISP optimizes image quality, supporting AI models like CNN and RNN, suitable for IoT and AIoT ecosystems.
aiWare represents aiMotive's advanced hardware intellectual property core for automotive neural network acceleration, pushing boundaries in efficiency and scalability. This neural processing unit (NPU) is tailored to meet the rigorous demands of automotive AI inference, providing robust support for various AI workloads, including CNNs, LSTMs, and RNNs. By achieving up to 256 Effective TOPS and remarkable scalability, aiWare caters to a wide array of applications, from edge processors in sensors to centralized high-performance modules.\n\nThe design of aiWare is particularly focused on enhancing efficiency in neural network operations, achieving up to 98% efficiency across diverse automotive applications. It features an innovative dataflow architecture, ensuring minimal external memory bandwidth usage while maximizing in-chip data processing. This reduces power consumption and enhances performance, making it highly adaptable for deployment in resource-critical environments.\n\nAdditionally, aiWare is embedded with comprehensive tools like the aiWare Studio SDK, which streamlines the neural network optimization and iteration process without requiring extensive NPU code adjustments. This ensures that aiWare can deliver optimal performance while minimizing development timelines by allowing for early performance estimations even before target hardware testing. Its integration into ASIL-B or higher certified solutions underscores aiWare's capability to power the most demanding safety applications in the automotive domain.
SAKURA-II is an advanced AI accelerator recognized for its efficiency and adaptability. It is specifically designed for edge applications that require rapid, real-time AI inference with minimal delay. Capable of processing expansive generative AI models such as Llama 2 and Stable Diffusion within an 8W power envelope, this accelerator supports a wide range of applications from vision to language processing. Its enhanced memory bandwidth and substantial DRAM capacity ensure its suitability for handling complex AI workloads, including large-scale language and vision models. The SAKURA-II platform also features robust power management, allowing it to achieve high efficiency during operations.
Wormhole is a high-efficiency processor designed to handle intensive AI processing tasks. Featuring an advanced architecture, it significantly accelerates AI workload execution, making it a key component for developers looking to optimize their AI applications. Wormhole supports an expansive range of AI models and frameworks, enabling seamless adaptation and deployment across various platforms. The processor’s architecture is characterized by high core counts and integrated system interfaces that facilitate rapid data movement and processing. This ensures that Wormhole can handle both single and multi-user environments effectively, especially in scenarios that demand extensive computational resources. The seamless connectivity supports vast memory pooling and distributed processing, enhancing AI application performance and scalability. Wormhole’s full integration with Tenstorrent’s open-source ecosystem further amplifies its utility, providing developers with the tools to fully leverage the processor’s capabilities. This integration facilitates optimized ML workflows and supports continuous enhancement through community contributions, making Wormhole a forward-thinking solution for cutting-edge AI development.
The C100 is designed to enhance IoT connectivity and performance with its highly integrated architecture. Built around a robust 32-bit RISC-V CPU running up to 1.5GHz, this chip offers powerful processing capabilities ideal for IoT applications. Its architecture includes embedded RAM and ROM memory, facilitating efficient data handling and computations. A prime feature of the C100 is its integration of Wi-Fi components and various transmission interfaces, enhancing its utility in diverse IoT environments. The inclusion of an ADC, LDO, and a temperature sensor supports myriad applications, ensuring devices can operate in a wide range of conditions and applications. The chip's low power consumption is a critical factor in this design, enabling longer operation duration in connected devices and reducing maintenance frequency due to less charging or battery replacement needs. This makes the C100 chip suitable for secure smart home systems, interactive toys, and healthcare devices.
The SCR7 is a 64-bit RISC-V application core crafted to meet high-performance demands of applications requiring powerful data processing. Featuring a sophisticated dual-issue pipeline with out-of-order execution, it enhances computational efficiency across varied tasks. The core is equipped with a robust floating-point unit and supports extensive RISC-V ISA extensions for advanced computing capabilities. SCR7's memory system includes L1 to L3 caches, with options for expansive up to 16MB L3 caching, ensuring data availability and integrity in demanding environments. Its multicore architecture supports up to eight cores, facilitating intensive computational tasks across industries such as AI and machine learning. Ideal for high-performance computing and big data applications, the SCR7 leverages its advanced interrupt systems and intelligent memory management for seamless operation. Comprehensive development resources, from simulators to SDKs, augment its integration across Linux-based systems, accelerating project development timelines.
The Hanguang 800 AI Accelerator by T-Head is an advanced semiconductor technology designed to accelerate AI computations and machine learning tasks. This accelerator is specifically optimized for high-performance inference, offering substantial improvements in processing times for deep learning applications. Its architecture is developed to leverage parallel computing capabilities, making it highly suitable for tasks that require fast and efficient data handling. This AI accelerator supports a broad spectrum of machine learning frameworks, ensuring compatibility with various AI algorithms. It is equipped with specialized processing units and a high-throughput memory interface, allowing it to handle large datasets with minimal latency. The Hanguang 800 is particularly effective in environments where rapid inferencing and real-time data processing are essential, such as in smart cities and autonomous driving. With its robust design and multi-faceted processing abilities, the Hanguang 800 Accelerator empowers industries to enhance their AI and machine learning deployments. Its capability to deliver swift computation and inference results ensures it is a valuable asset for companies looking to stay at the forefront of technological advancement in AI applications.
The GenAI v1-Q from RaiderChip brings forth a specialized focus on quantized AI operations, reducing memory requirements significantly while maintaining impressive precision and speed. This innovative accelerator is engineered to execute large language models in real-time, utilizing advanced quantization techniques such as Q4_K and Q5_K, thereby enhancing AI inference efficiency especially in memory-constrained environments. By offering a 276% boost in processing speed alongside a 75% reduction in memory footprint, GenAI v1-Q empowers developers to integrate advanced AI capabilities into smaller, less powerful devices without sacrificing operational quality. This makes it particularly advantageous for applications demanding swift response times and low latency, including real-time translation, autonomous navigation, and responsive customer interactions. The GenAI v1-Q diverges from conventional AI solutions by functioning independently, free from external network or cloud auxiliaries. Its design harmonizes superior computational performance with scalability, allowing seamless adaptation across variegated hardware platforms including FPGAs and ASIC implementations. This flexibility is crucial for tailoring performance parameters like model scale, inference velocity, and power consumption to meet exacting user specifications effectively. RaiderChip's GenAI v1-Q addresses crucial AI industry needs with its ability to manage multiple transformer-based models and confidential data securely on-premises. This opens doors for its application in sensitive areas such as defense, healthcare, and financial services, where confidentiality and rapid processing are paramount. With GenAI v1-Q, RaiderChip underscores its commitment to advancing AI solutions that are both environmentally sustainable and economically viable.
The Intelligence X280 is engineered to provide extensive capabilities for artificial intelligence and machine learning applications, emphasizing a software-first design approach. This high-performance processor supports vector and matrix computations, making it adept at handling the demanding workloads typical in AI-driven environments. With an extensive ALU and integrated VFPU capabilities, the X280 delivers superior data processing power. Capable of supporting complex AI tasks, the X280 processor leverages SiFive's advanced vector architecture to allow for high-speed data manipulation and precision. The core supports extensive vector lengths and offers compatibility with various machine learning frameworks, facilitating seamless deployment in both embedded and edge AI applications. The Intelligence family, represented by the X280, offers solutions that are not only scalable but are customizable to particular workload specifications. With high-bandwidth interfaces for connecting custom engines, this processor is built to evolve alongside AI's progressive requirements, ensuring relevance in rapidly changing technology landscapes.
The Topaz FPGA family by Efinix is crafted for high-performance, cost-efficient production volumes. Topaz FPGAs combine an advanced architecture with a low-power, high-volume design, suitable for mainstream applications. These devices integrate seamlessly into systems requiring robust protocol support, including PCIe Gen3, LVDS, and MIPI, making them ideal for machine vision, industrial automation, and wireless communications. These FPGAs are designed to pack more logic into a compact area, allowing for enhanced innovation and feature addition. The architecture facilitates seamless migration to higher performance Titanium FPGAs, making Topaz a flexible and future-proof choice for developers. With support for various BGAs, these units are easy to integrate, thus enhancing system design efficiency. Topaz FPGAs ensure product longevity and a stable supply chain, integral for applications characterized by long life cycles. This ensures systems maintain high efficiency and functionality over extended periods, aligning with Efinix’s commitment to offering durable and reliable semiconductor solutions for diverse market needs.
Micro Magic offers a state-of-the-art 64-bit RISC-V core known for its ultra-low power consumption, clocking in at just 10mW when operating at 1GHz. This processor harnesses advanced design techniques that allow it to achieve high performance while maintaining low operational voltages, optimizing energy efficiency. This processor stands out for its capability to deliver impressive processing speeds, reaching up to 5GHz under optimal conditions. It is designed with power conservation in mind, making it ideal for applications where energy efficiency is critical without sacrificing processing capability. The core is part of Micro Magic’s commitment to pushing the boundaries of low-power processing technology, making it suitable for a variety of high-speed computing tasks. Its design is particularly advantageous in environments demanding swift data processing and minimal power use, reaffirming Micro Magic’s reputation for pioneering efficient silicon solutions.
NeuroMosAIc Studio is a comprehensive software platform designed to maximize AI processor utilization through intuitive model conversion, mapping, simulation, and profiling. This advanced software suite supports Edge AI models by optimizing them for specific application needs. It offers precision analysis, network compression, and quantization tools to streamline the process of deploying AI models across diverse hardware setups. The platform is notably adept at integrating multiple AI functions and facilitating edge training processes. With tools like the NMP Compiler and Simulator, it allows developers to optimize functions at different stages, from quantization to training. The Studio's versatility is crucial for developers seeking to enhance AI solutions through customized model adjustments and optimization, ensuring high performance across AI systems. NeuroMosAIc Studio is particularly valuable for its edge training support and comprehensive optimization capabilities, paving the way for efficient AI deployment in various sectors. It offers a robust toolkit for AI model developers aiming to extract the maximum performance from hardware in dynamic environments.
The eSi-ADAS Radar IP Suite and Co-processor Engine is at the forefront of automotive and unmanned systems, enhancing radar detection and processing capabilities. It leverages cutting-edge signal processing technologies to provide accurate and rapid situational awareness, crucial for modern vehicles and aerial drones. With its comprehensive offering of radar algorithms, eSi-ADAS supports both traditional automotive radar applications and emerging unmanned aerial vehicle (UAV) platforms. This suite is crafted to meet the complex demands of real-time data processing and simultaneous multi-target tracking in dense environments, key for advanced driver-assistance systems. The co-processor engine within eSi-ADAS is highly efficient, designed to operate alongside existing vehicle systems with minimal additional power consumption. This suite is adaptable, supporting a wide range of vehicle architectures and operational scenarios, from urban driving to cross-country navigation.
The Veyron V1 CPU is designed to meet the demanding needs of data center workloads. Optimized for robust performance and efficiency, it handles a variety of tasks with precision. Utilizing RISC-V open architecture, the Veyron V1 is easily integrated into custom high-performance solutions. It aims to support the next-generation data center architectures, promising seamless scalability for various applications. The CPU is crafted to compete effectively against ARM and x86 data center CPUs, providing the same class-leading performance with added flexibility for bespoke integrations.
Tensix Neo represents the next evolution in AI processing, offering robust capabilities for handling modern AI challenges. Its design focuses on maximizing performance while maintaining efficiency, a crucial aspect in AI and machine learning environments. Tensix Neo facilitates advanced computation across multiple frameworks, supporting a range of AI applications. Featuring a strategic blend of core architecture and integrated memory, Tensix Neo excels in both processing speed and capacity, essential for handling comprehensive AI workloads. Its architecture supports multi-threaded operations, optimizing performance for parallel computing scenarios, which are common in AI tasks. Tensix Neo's seamless connection with Tenstorrent's open-source software environment ensures that developers can quickly adapt it to their specific needs. This interconnectivity not only boosts operational efficiency but also supports continuous improvements and feature expansions through community contributions, positioning Tensix Neo as a versatile solution in the landscape of AI technology.
The CTAccel Image Processor on Intel Agilex FPGA is designed to handle high-performance image processing by capitalizing on the robust capabilities of Intel's Agilex FPGAs. These FPGAs, leveraging the 10 nm SuperFin process technology, are ideal for applications demanding high performance, power efficiency, and compact sizes. Featuring advanced DSP blocks and high-speed transceivers, this IP thrives in accelerating image processing tasks that are typically computational-intensive when executed on CPUs. One of the main advantages is its ability to significantly enhance image processing throughput, achieving up to 20 times the speed while maintaining reduced latency. This performance prowess is coupled with low power consumption, leading to decreased operational and maintenance costs due to fewer required server instances. Additionally, the solution is fully compatible with mainstream image processing software, facilitating seamless integration and leveraging existing software investments. The adaptability of the FPGA allows for remote reconfiguration, ensuring that the IP can be tailored to specific image processing scenarios without necessitating a server reboot. This ease of maintenance, combined with a substantial boost in compute density, underscores the IP's suitability for high-demand image processing environments, such as those encountered in data centers and cloud computing platforms.
CodaCache delivers high efficiency in SoC environments by serving as a highly configurable last-level cache. It addresses design challenges related to performance and power use by effectively managing data access and system scalability. Supporting flexible configurations, the IP adapts seamlessly into various SoC layouts, optimizing memory latency and power consumption. The strategic use of CodaCache in tandem with Arteris's NoC solutions enhances overall system performance, allowing for smoother data flow and faster processing speeds while mitigating bottlenecks.
The Spiking Neural Processor T1 is a microcontroller tailored for ultra-low-power applications demanding high-performance pattern recognition at the sensor edge. It features an advanced neuromorphic architecture that leverages spiking neural network engines combined with RISC-V core capabilities. This architecture allows for sub-milliwatt power dissipation and sub-millisecond latency, enabling the processor to conduct real-time analysis and identification of embedded patterns in sensor data while operating in always-on scenarios. Additionally, the T1 provides diverse interfaces, making it adaptable for use with various sensor types.
The KL720 is engineered for high efficiency, achieving up to 0.9 TOPS per Watt, setting it apart in the edge AI marketplace. Designed for real-world scenarios where power efficiency is paramount, this chip supports high-end IP cameras, smart TVs, and AI-enabled devices like glasses and headsets. Its ARM Cortex M4 CPU facilitates the processing of complex tasks like 4K image handling, full HD video, and 3D sensing, making it versatile for applications that include gaming and AI-assisted interactions.
The CTAccel Image Processor for Xilinx's Alveo U200 is a FPGA-based accelerator aimed at enhancing image processing workloads in server environments. Utilizing the powerful capabilities of the Alveo U200 FPGA, this processor dramatically boosts throughput and reduces processing latency for data centers. The accelerator can vastly increase image processing speed, up to 4 to 6 times that of traditional CPUs, and decrease latency likewise, ensuring that compute density in a server setting is significantly boosted. This performance uplift enables data centers to lower maintenance and operational costs due to reduced hardware requirements. Furthermore, this IP maintains full compatibility with popular image processing software like OpenCV and ImageMagick, ensuring smooth adaptation for existing workflows. The advanced FPGA partial reconfiguration technology allows for dynamic updates and adjustments, increasing the IP's pragmatism for a wide array of image-related applications and improving overall performance without the need for server reboots.
ISPido represents a fully configurable RTL Image Signal Processing Pipeline, adhering to the AMBA AXI4 standards and tailored through the AXI4-LITE protocol for seamless integration with systems such as RISC-V. This advanced pipeline supports a variety of image processing functions like defective pixel correction, color filter interpolation using the Malvar-Cutler algorithm, and auto-white balance, among others. Designed to handle resolutions up to 7680x7680, ISPido provides compatibility for both 4K and 8K video systems, with support for 8, 10, or 12-bit depth inputs. Each module within this pipeline can be fine-tuned to fit specific requirements, making it a versatile choice for adapting to various imaging needs. The architecture's compatibility with flexible standards ensures robust performance and adaptability in diverse applications, from consumer electronics to professional-grade imaging solutions. Through its compact design, ISPido optimizes area and energy efficiency, providing high-quality image processing while keeping hardware demands low. This makes it suitable for battery-operated devices where power efficiency is crucial, without sacrificing the processing power needed for high-resolution outputs.
The RAIV General Purpose GPU (GPGPU) epitomizes versatility and cutting-edge technology in the realm of data processing and graphics acceleration. It serves as a crucial technology enabler for various prominent sectors that are central to the fourth industrial revolution, such as autonomous driving, IoT, virtual reality/augmented reality (VR/AR), and sophisticated data centers. By leveraging the RAIV GPGPU, industries are able to process vast amounts of data more efficiently, which is paramount for their growth and competitive edge. Characterized by its advanced architectural design, the RAIV GPU excels in managing substantial computational loads, which is essential for AI-driven processes and complex data analytics. Its adaptability makes it suitable for a wide array of applications, from enhancing automotive AI systems to empowering VR environments with seamless real-time interaction. Through optimized data handling and acceleration, the RAIV GPGPU assists in realizing smoother and more responsive application workflows. The strategic design of the RAIV GPGPU focuses on enabling integrative solutions that enhance performance without compromising on power efficiency. Its functionality is built to meet the high demands of today’s tech ecosystems, fostering advancements in computational efficiency and intelligent processing capabilities. As such, the RAIV stands out not only as a tool for improved graphical experiences but also as a significant component in driving innovation within tech-centric industries worldwide. Its pioneering architecture thus supports a multitude of applications, ensuring it remains a versatile and indispensable asset in diverse technological landscapes.
The Codasip RISC-V BK Core Series is designed to offer highly performant solutions suitable for a range of tasks from embedded applications to more demanding compute environments. By leveraging the RISC-V architecture, the BK Core Series provides a balance of power efficiency and processing capability, which is ideal for IoT edge applications and sensor controllers. The series is built around the philosophy of flexibility, allowing for modifications and enhancements to meet specific application requirements, including the integration of custom instructions to accommodate special workloads. This series also supports functional safety and security measures as outlined by industry standards, ensuring a robust foundation for critical applications.
The Azurite Core-hub by InCore Semiconductors is a sophisticated solution designed to offer scalable RISC-V SoCs with high-speed secure interconnect capabilities. This processor is tailored for performance-demanding applications, ensuring that systems maintain robust security while executing tasks at high speeds. Azurite leverages advanced interconnect technologies to enhance the communication between components within a SoC, making it ideal for industries that require rapid data transfer and high processing capabilities. The core is engineered to be scalable, supporting a wide range of applications from edge AI to functional safety systems, adapting seamlessly to various industry needs. Engineered with a focus on security, the Azurite Core-hub incorporates features that protect data integrity and system operation in a dynamic technological landscape. This makes it a reliable choice for companies seeking to integrate advanced RISC-V architectures into their security-focused applications, offering not just innovation but also peace of mind with its secure design.
Dyumnin Semiconductors' RISCV SoC is a robust solution built around a 64-bit quad-core server-class RISC-V CPU, designed to meet advanced computing demands. This chip is modular, allowing for the inclusion of various subsystems tailored to specific applications. It integrates a sophisticated AI/ML subsystem that features an AI accelerator tightly coupled with a TensorFlow unit, streamlining AI operations and enhancing their efficiency. The SoC supports a multimedia subsystem equipped with IP for HDMI, Display Port, and MIPI, as well as camera and graphic accelerators for comprehensive multimedia processing capabilities. Additionally, the memory subsystem includes interfaces for DDR, MMC, ONFI, NorFlash, and SD/SDIO, ensuring compatibility with a wide range of memory technologies available in the market. This versatility makes it a suitable choice for devices requiring robust data storage and retrieval capabilities. To address automotive and communication needs, the chip's automotive subsystem provides connectivity through CAN, CAN-FD, and SafeSPI IPs, while the communication subsystem supports popular protocols like PCIe, Ethernet, USB, SPI, I2C, and UART. The configurable nature of this SoC allows for the adaptation of its capabilities to meet specific end-user requirements, making it a highly flexible tool for diverse applications.
Trion FPGAs by Efinix are engineered for the fast-paced edge and IoT markets. Built on a 40 nm process, these FPGAs offer a wide range of logic density from 4K to 120K logic elements. They bring power-performance-area advantages for general-purpose custom logic applications, including mobile and IoT markets, while also enhancing computing capabilities in emerging technologies such as deep learning and edge computing. The Trion family is known for its small packages, which enable its deployment in highly integrated systems. Features such as the DDR DRAM Controller and MIPI CSI-2 Controller are hardened into the architecture, ensuring smooth data management and transfer in applications that demand real-time processing. This makes Trion FPGAs an excellent choice for various industrial, medical, and consumer applications where space and power efficiency are critical. With a focus on longevity, Efinix supports Trion FPGAs with a stable product lifecycle, aligning with market requirements for dependable, production-ready solutions. These FPGAs are versatile enough to serve applications in edge computing, video processing, industrial automation, and more, offering a complete system solution with their embedded interfaces and soft processor systems.
The RWM6050 Baseband Modem is a cutting-edge component designed for high-efficiency wireless communications, ideally suited for dense data transmission environments. This modem acts as a fundamental building block within Blu Wireless's product portfolio, enabling seamless integration into various network architectures. Focusing on addressing the needs of complex wireless systems, the RWM6050 optimizes data flow and enhances connectivity capabilities within mmWave deployments. Technical proficiency is at the core of RWM6050's design, targeting high-speed data processing and signal integrity. It supports multiple communication standards, ensuring compatibility and flexibility in diverse operational settings. The modem's architecture is crafted to manage substantial data payloads effectively, fostering reliable, high-bandwidth communication across different sectors, including telecommunications and IoT applications. The RWM6050 is engineered to simplify the setup of communication networks and improve performance in crowded signal environments. Its robust design not only accommodates the challenges posed by demanding applications but also anticipates future advancements within wireless communication technologies. The modem provides a scalable yet efficient solution that meets the industry's evolving requirements.
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