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.
Akida's Neural Processor IP represents a leap in AI architecture design, tailored to provide exceptional energy efficiency and processing speed for an array of edge computing tasks. At its core, the processor mimics the synaptic activity of the human brain, efficiently executing tasks that demand high-speed computation and minimal power usage. This processor is equipped with configurable neural nodes capable of supporting innovative AI frameworks such as convolutional and fully-connected neural network processes. Each node accommodates a range of MAC operations, enhancing scalability from basic to complex deployment requirements. This scalability enables the development of lightweight AI solutions suited for consumer electronics as well as robust systems for industrial use. Onboard features like event-based processing and low-latency data communication significantly decrease the strain on host processors, enabling faster and more autonomous system responses. Akida's versatile functionality and ability to learn on the fly make it a cornerstone for next-generation technology solutions that aim to blend cognitive computing with practical, real-world applications.
The KL730 is a third-generation AI chip that integrates advanced reconfigurable NPU architecture, delivering up to 8 TOPS of computing power. This cutting-edge technology enhances computational efficiency across a range of applications, including CNN and transformer networks, while minimizing DDR bandwidth requirements. The KL730 also boasts enhanced video processing capabilities, supporting 4K 60FPS outputs. With expertise spanning over a decade in ISP technology, the KL730 stands out with its noise reduction, wide dynamic range, fisheye correction, and low-light imaging performance. It caters to markets like intelligent security, autonomous vehicles, video conferencing, and industrial camera systems, among others.
The second-generation Akida platform builds upon the foundation of its predecessor with enhanced computational capabilities and increased flexibility for a broader range of AI and machine learning applications. This version supports 8-bit weights and activations in addition to the flexible 4- and 1-bit operations, making it a versatile solution for high-performance AI tasks. Akida 2 introduces support for programmable activation functions and skip connections, further enhancing the efficiency of neural network operations. These capabilities are particularly advantageous for implementing sophisticated machine learning models that require complex, interconnected processing layers. The platform also features support for Spatio-Temporal and Temporal Event-Based Neural Networks, advancing its application in real-time, on-device AI scenarios. Built as a silicon-proven, fully digital neuromorphic solution, Akida 2 is designed to integrate seamlessly with various microcontrollers and application processors. Its highly configurable architecture offers post-silicon flexibility, making it an ideal choice for developers looking to tailor AI processing to specific application needs. Whether for low-latency video processing, real-time sensor data analysis, or interactive voice recognition, Akida 2 provides a robust platform for next-generation AI developments.
The Metis AIPU PCIe AI Accelerator Card is engineered for developers demanding superior AI performance. With its quad-core Metis AIPU, this card delivers up to 214 TOPS, tackling challenging vision applications with unmatched efficiency. The PCIe card is designed with user-friendly integration in mind, featuring the Voyager SDK software stack that accelerates application deployment. Offering impressive processing speeds, the card supports up to 3,200 FPS for ResNet-50 models, providing a competitive edge for demanding AI tasks. Its design ensures it meets the needs of a wide array of AI applications, allowing for scalability and adaptability in various use cases.
The Akida IP is a groundbreaking neural processor designed to emulate the cognitive functions of the human brain within a compact and energy-efficient architecture. This processor is specifically built for edge computing applications, providing real-time AI processing for vision, audio, and sensor fusion tasks. The scalable neural fabric, ranging from 1 to 128 nodes, features on-chip learning capabilities, allowing devices to adapt and learn from new data with minimal external inputs, enhancing privacy and security by keeping data processing localized. Akida's unique design supports 4-, 2-, and 1-bit weight and activation operations, maximizing computational efficiency while minimizing power consumption. This flexibility in configuration, combined with a fully digital neuromorphic implementation, ensures a cost-effective and predictable design process. Akida is also equipped with event-based acceleration, drastically reducing the demands on the host CPU by facilitating efficient data handling and processing directly within the sensor network. Additionally, Akida's on-chip learning supports incremental learning techniques like one-shot and few-shot learning, making it ideal for applications that require quick adaptation to new data. These features collectively support a broad spectrum of intelligent computing tasks, including object detection and signal processing, all performed at the edge, thus eliminating the need for constant cloud connectivity.
The Yitian 710 Processor is a groundbreaking component in processor technology, designed with cutting-edge architecture to enhance computational efficiency. This processor is tailored for cloud-native environments, offering robust support for high-demand computing tasks. It is engineered to deliver significant improvements in performance, making it an ideal choice for data centers aiming to optimize their processing power and energy efficiency. With its advanced features, the Yitian 710 stands at the forefront of processor innovation, ensuring seamless integration with diverse technology platforms and enhancing the overall computing experience across industries.
MetaTF is BrainChip's premier development tool platform designed to complement its neuromorphic technology solutions. This platform is a comprehensive toolkit that empowers developers to convert and optimize standard machine learning models into formats compatible with BrainChip's Akida technology. One of its key advantages is its ability to adjust models into sparse formats, enhancing processing speed and reducing power consumption. The MetaTF framework provides an intuitive interface for integrating BrainChip’s specialized AI capabilities into existing workflows. It supports streamlined adaptation of models to ensure they are optimized for the unique characteristics of neuromorphic processing. Developers can utilize MetaTF to rapidly iterate and refine AI models, making the deployment process smoother and more efficient. By providing direct access to pre-trained models and tuning mechanisms, MetaTF allows developers to capitalize on the benefits of event-based neural processing with minimal configuration effort. This platform is crucial for advancing the application of machine learning across diverse fields such as IoT devices, healthcare technology, and smart infrastructure.
The AI Camera Module from Altek is a versatile, high-performance component designed to meet the increasing demand for smart vision solutions. This module features a rich integration of imaging lens design and combines both hardware and software capacities to create a seamless operational experience. Its design is reinforced by Altek's deep collaboration with leading global brands, ensuring a top-tier product capable of handling diverse market requirements. Equipped to cater to AI and IoT interplays, the module delivers outstanding capabilities that align with the expectations for high-resolution imaging, making it suitable for edge computing applications. The AI Camera Module ensures that end-user diversity is meaningfully addressed, offering customization in device functionality which supports advanced processing requirements such as 2K and 4K video quality. This module showcases Altek's prowess in providing comprehensive, all-in-one camera solutions which leverage sophisticated imaging and rapid processing to handle challenging conditions and demands. The AI Camera's technical blueprint supports complex AI algorithms, enhancing not just image quality but also the device's interactive capacity through facial recognition and image tracking technology.
The Veyron V2 CPU represents Ventana's second-generation RISC-V high-performance processor, designed for cloud, data center, edge, and automotive applications. This processor offers outstanding compute capabilities with its server-class architecture, optimized for handling complex, virtualized, and cloud-native workloads efficiently. The Veyron V2 is available as both IP for custom SoCs and as a complete silicon platform, ensuring flexibility for integration into various technological infrastructures. Emphasizing a modern architectural design, it includes full compliance with RISC-V RVA23 specifications, showcasing features like high Instruction Per Clock (IPC) and power-efficient architectures. Comprising of multiple core clusters, this CPU is capable of delivering superior AI and machine learning performance, significantly boosting throughput and energy efficiency. The Veyron V2's advanced fabric interconnects and extensive cache architecture provide the necessary infrastructure for high-performance applications, ensuring broad market adoption and versatile deployment options.
The Quadric Chimera General Purpose Neural Processing Unit (GPNPU) delivers unparalleled performance for AI workloads, characterized by its ability to handle diverse and complex tasks without requiring separate processors for different operations. Designed to unify AI inference and traditional computing processes, the GPNPU supports matrix, vector, and scalar tasks within a single, cohesive execution pipeline. This design not only simplifies the integration of AI capabilities into system-on-chip (SoC) architectures but also significantly boosts developer productivity by allowing them to focus on optimizing rather than partitioning code. The Chimera GPNPU is highly scalable, supporting a wide range of operations across all market segments, including automotive applications with its ASIL-ready versions. With a performance range from 1 to 864 TOPS, it excels in running the latest AI models, such as vision transformers and large language models, alongside classic network backbones. This flexibility ensures that devices powered by Chimera GPNPU can adapt to advancing AI trends, making them suitable for applications that require both immediate performance and long-term capability. A key feature of the Chimera GPNPU is its fully programmable nature, making it a future-proof solution for deploying cutting-edge AI models. Unlike traditional NPUs that rely on hardwired operations, the Chimera GPNPU uses a software-driven approach with its source RTL form, making it a versatile option for inference in mobile, automotive, and edge computing applications. This programmability allows for easy updating and adaptation to new AI model operators, maximizing the lifespan and relevance of chips that utilize this technology.
The xcore.ai platform by XMOS is a versatile, high-performance microcontroller designed for the integration of AI, DSP, and real-time I/O processing. Focusing on bringing intelligence to the edge, this platform facilitates the construction of entire DSP systems using software without the need for multiple discrete chips. Its architecture is optimized for low-latency operation, making it suitable for diverse applications from consumer electronics to industrial automation. This platform offers a robust set of features conducive to sophisticated computational tasks, including support for AI workloads and enhanced control logic. The xcore.ai platform streamlines development processes by providing a cohesive environment that blends DSP capabilities with AI processing, enabling developers to realize complex applications with greater efficiency. By doing so, it reduces the complexity typically associated with chip integration in advanced systems. Designed for flexibility, xcore.ai supports a wide array of applications across various markets. Its ability to handle audio, voice, and general-purpose processing makes it an essential building block for smart consumer devices, industrial control systems, and AI-powered solutions. Coupled with comprehensive software support and development tools, the xcore.ai ensures a seamless integration path for developers aiming to push the boundaries of AI-enabled technologies.
The Metis AIPU M.2 Accelerator Module is designed for devices that require high-performance AI inference in a compact form factor. Powered by a quad-core Metis AI Processing Unit (AIPU), this module optimizes power consumption and integration, making it ideal for AI-driven applications. With a dedicated memory of 1 GB DRAM, it enhances the capabilities of vision processing systems, providing significant boosts in performance for devices with Next Generation Form Factor (NGFF) M.2 sockets. Ideal for use in computer vision systems and more, it offers hassle-free integration and evaluation with Axelera's Voyager SDK. This accelerator module is tailored for any application seeking to harness the power of AI processing efficiently. The Metis AIPU M.2 Module streamlines the deployment of AI applications, ensuring high performance with reduced power consumption.
The Talamo Software Development Kit (SDK) is an advanced solution from Innatera designed to expedite the development of neuromorphic AI applications. It integrates seamlessly with PyTorch, providing developers with a familiar environment to build and extend AI models specifically for spiking neural processors. By enhancing the standard PyTorch workflow, Talamo simplifies the complexity associated with constructing spiking neural networks, allowing a broader range of developers to create sophisticated AI solutions without requiring deep expertise in neuromorphic computing. Talamo's capabilities include automatic mapping of trained models onto Innatera's heterogeneous computing architecture, coupled with a robust architecture simulator for efficient validation and iteration. This means developers can iterate quickly and efficiently, optimizing their applications for performance and power without extensive upfront reconfiguration or capital layout. The SDK supports the creation of collaborative application pipelines that merge signal processing with AI, supporting custom functions and neural network implementation. This gives developers the flexibility to tailor solutions to specific needs, be it in audio processing, gesture recognition, or environmental sensing. Through its comprehensive toolkit, Talamo SDK empowers users to translate conceptual models into high-performing AI applications that leverage the unique processing strengths of spiking neural networks, ultimately lowering barriers to innovation in low-power, edge-based AI.
The aiWare NPU (Neural Processing Unit) by aiMotive is a high-performance hardware solution tailored specifically for automotive AI applications. It is engineered to accelerate inference tasks for autonomous driving systems, ensuring excellent performance across a variety of neural network workloads. aiWare delivers significant flexibility and efficiency, capable of scaling from basic Level 2 applications to complex multi-sensor Level 3+ systems. Achieving up to 98% efficiency, aiWare's design focuses on minimizing power utilization while maximizing core performance. It supports a broad spectrum of neural network architectures, including convolutional neural networks, transformers, and recurrent networks, making it suitable for diverse AI tasks in the automotive sphere. The NPU's architecture allows for minimal external memory access, thanks to its highly efficient dataflow design that capitalizes on on-chip memory caching. With a robust toolkit known as aiWare Studio, engineers can efficiently optimize neural networks without in-depth knowledge of low-level programming, streamlining development and integration efforts. The aiWare hardware is also compatible with V2X communication and advanced driver assistance systems, adapting to various operational needs with great dexterity. Its comprehensive support for automotive safety standards further cements its reputation as a reliable choice for integrating artificial intelligence into next-generation vehicles.
The SAKURA-II is a cutting-edge AI accelerator that combines high performance with low power consumption, designed to efficiently handle multi-billion parameter models for generative AI applications. It is particularly suited for tasks that demand real-time AI inferencing with minimal batch processing, making it ideal for applications devoted to edge environments. With a typical power usage of 8 watts and a compact footprint, the SAKURA-II achieves more than twice the AI compute efficiency of comparable solutions. This AI accelerator supports next-generation applications by providing up to 4x more DRAM bandwidth compared to alternatives, crucial for the processing of complex vision tasks and large language models (LLMs). The hardware offers advanced precision through software-enabled mixed-precision, which achieves near FP32 accuracy, while a unique sparse computing feature optimizes memory usage. Its robust memory architecture backs up to 32GB of DRAM, providing ample capacity for intensive AI workloads. The SAKURA-II's modular design allows it to be used in multiple form factors, addressing the diverse needs of modern computing tasks such as those found in smart cities, autonomous robotics, and smart manufacturing. Its adaptability is further enhanced by runtime configurable data paths, allowing the device to optimize task scheduling and resource allocation dynamically. These features are powered by the Dynamic Neural Accelerator engine, ensuring efficient computation and energy management.
The RV12 RISC-V Processor is a highly configurable, single-core CPU that adheres to RV32I and RV64I standards. It’s engineered for the embedded market, offering a robust structure based on the RISC-V instruction set. The processor's architecture allows simultaneous instruction and data memory accesses, lending itself to a broad range of applications and maintaining high operational efficiency. This flexibility makes it an ideal choice for diverse execution requirements, supporting efficient data processing through an optimized CPU framework. Known for its adaptability, the RV12 processor can support multiple configurations to suit various application demands. It is capable of providing the necessary processing power for embedded systems, boasting a reputation for stability and reliability. This processor becomes integral for designs that require a maintainability of performance without compromising on the configurability aspect, meeting the rigorous needs of modern embedded computing. The processor's support of the open RISC-V architecture ensures its capability to integrate into existing systems seamlessly. It lends itself well to both industrial and academic applications, offering a resource-efficient platform that developers and researchers can easily access and utilize.
The KL630 is a pioneering AI chipset featuring Kneron's latest NPU architecture, which is the first to support Int4 precision and transformer networks. This cutting-edge design ensures exceptional compute efficiency with minimal energy consumption, making it ideal for a wide array of applications. With an ARM Cortex A5 CPU at its core, the KL630 excels in computation while maintaining low energy expenditure. This SOC is designed to handle both high and low light conditions optimally and is perfectly suited for use in diverse edge AI devices, from security systems to expansive city and automotive networks.
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.
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.
Micro Magic's Ultra-Low-Power 64-Bit RISC-V Core is engineered for superior energy efficiency, consuming a mere 10mW while operating at a clock speed of 1GHz. This processor core is designed to excel under low voltage conditions, delivering high performance without compromising on power conservation. It is ideal for applications requiring prolonged battery life or those operating in energy-sensitive environments. This processor integrates Micro Magic's advanced design methodologies, allowing for operation at frequencies up to 5GHz when necessary. The RISC-V Core capabilities are enhanced by solid construction, ensuring reliability and robust performance across various use-cases, making it an adaptable solution for modern electronic designs. With its cutting-edge design, this RISC-V core supports rapid deployment in numerous applications, especially in areas demanding high computational power alongside reduced energy usage. Micro Magic's advanced techniques ensure that this core is not only fast but also supports scalable integration into various systems with ease.
The Hanguang 800 AI Accelerator is a high-performance AI processor developed to meet the complex demands of artificial intelligence workloads. This accelerator is engineered with cutting-edge AI processing capabilities, enabling rapid data analysis and machine learning model inference. Designed for flexibility, the Hanguang 800 delivers superior computation speed and energy efficiency, making it an optimal choice for AI applications in a variety of sectors, from data centers to edge computing. By supporting high-volume data throughput, it enables organizations to achieve significant advantages in speed and efficiency, facilitating the deployment of intelligent solutions.
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 KL520 marks Kneron's foray into the edge AI landscape, offering an impressive combination of size, power efficiency, and performance. Armed with dual ARM Cortex M4 processors, this chip can operate independently or as a co-processor to enable AI functionalities such as smart locks and security monitoring. The KL520 is adept at 3D sensor integration, making it an excellent choice for applications in smart home ecosystems. Its compact design allows devices powered by it to operate on minimal power, such as running on AA batteries for extended periods, showcasing its exceptional power management capabilities.
The KL530 represents a significant advancement in AI chip technology with a new NPU architecture optimized for both INT4 precision and transformer networks. This SOC is engineered to provide high processing efficiency and low power consumption, making it suitable for AIoT applications and other innovative scenarios. It features an ARM Cortex M4 CPU designed for low-power operation and offers a robust computational power of up to 1 TOPS. The chip's ISP enhances image quality, while its codec ensures efficient multimedia compression. Notably, the chip's cold start time is under 500 ms with an average power draw of less than 500 mW, establishing it as a leader in energy efficiency.
Crafted to deliver significant power savings, the Tianqiao-70 is a low-power RISC-V CPU that excels in commercial-grade scenarios. This 64-bit CPU core is primarily designed for applications where power efficiency is critical, such as mobile devices and computationally intensive IoT solutions. The core's architecture is specifically optimized to perform under stringent power budgets without compromising on the processing power needed for complex tasks. It provides an efficient solution for scenarios that demand reliable performance while maintaining a low energy footprint. Through its refined design, the Tianqiao-70 supports a broad spectrum of applications, including personal computing, machine learning, and mobile communications. Its versatility and power-awareness make it a preferred choice for developers focused on sustainable and scalable computing architectures.
Himax's WiseEye2 AI solution is a pioneering technology aimed at ultra-low power sensor fusion for AI on-device applications. This innovative solution integrates artificial intelligence capabilities within consumer electronics, offering smart solutions for homes, cities, and various industrial applications. The WiseEye2 technology excels in enabling devices to perform complex AI tasks onsite without relying heavily on remote data centers. This feature not only minimizes latency but also enhances privacy aspects by processing data locally. It supports a range of applications from smart home appliances and intelligent security systems to cutting-edge consumer electronics. Designed with efficiency in mind, the WiseEye2 AI solution is built to operate under minimal power conditions, extending the battery life of devices it powers. This makes it ideal for portable and remote applications where energy conservation is critical.
The NMP-750 is AiM Future's powerful edge computing accelerator designed specifically for high-performance tasks. With up to 16 TOPS of computational throughput, this accelerator is perfect for automotive, AMRs, UAVs, as well as AR/VR applications. Fitted with up to 16 MB of local memory and featuring RISC-V or Arm Cortex-R/A 32-bit CPUs, it supports diverse data processing requirements crucial for modern technological solutions. The versatility of the NMP-750 is displayed in its ability to manage complex processes such as multi-camera stream processing and spectral efficiency management. It is also an apt choice for applications that require energy management and building automation, demonstrating exceptional potential in smart city and industrial setups. With its robust architecture, the NMP-750 ensures seamless integration into systems that need to handle large data volumes and support high-speed data transmission. This makes it ideal for applications in telecommunications and security where infrastructure resilience is paramount.
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.
The EW6181 is an advanced multi-GNSS silicon solution designed for high sensitivity and precision. This powerful chip supports GPS, Glonass, BeiDou, Galileo, SBAS, and A-GNSS, offering integration flexibility with various applications. Its built-in RF frontend and digital baseband facilitate robust signal processing, controlled by an ARM MCU. The EW6181 integrates essential interfaces for diverse connectivity, matched with DC-DC converters and LDOs to minimize BOM in battery-driven setups. This silicon marries low power demands with strong functional capabilities, thanks to proprietary algorithms that optimize its operation. It’s engineered to deliver exceptional accuracy and sensitivity in both standalone and cloud-related environments, adapting smoothly to connected ecosystems for enhanced efficiency. Its compact silicon footprint further enhances its suitability for applications needing prolonged battery life and reliable positioning. With a focus on Antenna Diversity, the EW6181 shines in dynamic applications like action cameras and smartwatches, ensuring clear signal reception even when devices rapidly rotate. This aspect accentuates the chip's ability to maintain consistent performance across a range of challenging environments, reinforcing its role in the forefront of GNSS technology.
RAIV represents Siliconarts' General Purpose-GPU (GPGPU) offering, engineered to accelerate data processing across diverse industries. This versatile GPU IP is essential in sectors engaged in high-performance computing tasks, such as autonomous driving, IoT, and sophisticated data centers. With RAIV, Siliconarts taps into the potential of the fourth industrial revolution, enabling rapid computation and seamless data management. The RAIV architecture is poised to deliver unmatched efficiency in high-demand scenarios, supporting massive parallel processing and intricate calculations. It provides an adaptable framework that caters to the needs of modern computing, ensuring balanced workloads and optimized performance. Whether used for VR/AR applications or supporting the back-end infrastructure of data-intensive operations, RAIV is designed to meet and exceed industry expectations. RAIV’s flexible design can be tailored to enhance a broad spectrum of applications, promising accelerated innovation in sectors dependent on AI and machine learning. This GPGPU IP not only underscores Siliconarts' commitment to technological advancement but also highlights its capability to craft solutions that drive forward computational boundaries.
The Neural Processing Unit (NPU) offered by OPENEDGES is engineered to accelerate machine learning tasks and AI computations. Designed for integration into advanced processing platforms, this NPU enhances the ability of devices to perform complex neural network computations quickly and efficiently, significantly advancing AI capabilities. This NPU is built to handle both deep learning and inferencing workloads, utilizing highly efficient data management processes. It optimizes the execution of neural network models with acceleration capabilities that reduce power consumption and latency, making it an excellent choice for real-time AI applications. The architecture is flexible and scalable, allowing it to be tailored for specific application needs or hardware constraints. With support for various AI frameworks and models, the OPENEDGES NPU ensures compatibility and smooth integration with existing AI solutions. This allows companies to leverage cutting-edge AI performance without the need for drastic changes to legacy systems, making it a forward-compatible and cost-effective solution for modern AI applications.
aiSim 5 is a state-of-the-art automotive simulation platform designed for ADAS and autonomous driving testing. Recognized as the world's first ISO26262 ASIL-D certified simulator, it offers unparalleled accuracy and determinism in simulating various driving scenarios and environmental conditions. The simulator integrates AI-based digital twin technology and an advanced rendering engine to create realistic traffic scenarios, helping engineers verify and validate driver assistance systems. Harnessing powerful physics-based simulation capabilities, aiSim 5 replicates real-world phenomena like weather effects and complex traffic dynamics with precision. By offering a comprehensive set of 3D assets and scenarios, it allows for the extensive testing of systems in both typical and edge conditions. With its flexible and open architecture, aiSim 5 can seamlessly integrate into existing testing toolchains, supporting significant variations in sensor configurations and driving algorithms. The platform encourages innovation in simulation methodologies by providing tools for scenario randomization and synthetic data generation, crucial for developing resilient ADAS applications. Additionally, its cloud-ready architecture makes it applicable across various hardware platforms, turning simulation into a versatile resource available on inexpensive or high-end computing configurations alike.
The Codasip RISC-V BK Core Series is designed to offer flexible and high-performance core options catering to a wide range of applications, from low-power tasks to intricate computational needs. This series achieves optimal balance in power consumption and processing speed, making it suitable for applications demanding energy efficiency without compromising performance. These cores are fully RISC-V compliant, allowing for easy customizations to suit specific needs by modifying the processor's architecture or instruction set through Codasip Studio. The BK Core Series provides a streamlining process for developing precise computing solutions, ideal for IoT edge devices and sensor controllers where both small area and low power are critical. Moreover, the BK Core Series supports architectural exploration, enabling users to optimize the core design specifically tailored to their applications. This capability ensures that each core delivers the expected power, efficiency, and performance metrics required by modern technological solutions.
The KL720 AI SoC is designed for optimal performance-to-power ratios, achieving 0.9 TOPS per watt. This makes it one of the most efficient chips available for edge AI applications. The SOC is crafted to meet high processing demands, suitable for high-end devices including smart TVs, AI glasses, and advanced cameras. With an ARM Cortex M4 CPU, it enables superior 4K imaging, full HD video processing, and advanced 3D sensing capabilities. The KL720 also supports natural language processing (NLP), making it ideal for emerging AI interfaces such as AI assistants and gaming gesture controls.
The H.264 FPGA Encoder and CODEC micro footprint cores are a compact and fast solution for video compression, specifically tailored for FPGAs. This licensable IP cores support 1080p60 H.264 Baseline encoding with a single core, offering various configurations such as an H.264 Encoder, CODEC, and I-Frame Only Encoder. These cores are renowned for their small size and rapid processing capabilities, designed to be ITAR compliant for secure applications. Developers can customize these cores to achieve desired pixel depths and resolutions, ensuring adaptability to diverse project needs. With an exceptionally low 1ms latency at 1080p30, these cores are acclaimed as industry-leading in terms of both size and performance. They enhance efficiency by providing fast video processing solutions without compromising quality. The cores are particularly useful in applications demanding high-speed and high-resolution video compression in FPGA implementations. These H.264 cores come with the option for a low-cost evaluation license, providing a seamless entry into advanced video processing tasks. With customizable features, they represent a versatile choice for engineers working on applications involving intensive video encoding and decoding needs.
The RISC-V Core IP developed by AheadComputing Inc. stands out in the field of 64-bit application processors. Designed to deliver exceptional per-core performance, this processor is engineered with the highest standards to maximize the Instructions Per Cycle (IPC) efficiency. AheadComputing's RISC-V Core IP is continuously refined to address the growing demands of high-performance computing applications. The innovative architecture of this core allows for seamless execution of complex algorithms while achieving superior speed and efficiency. This design is crucial for applications that require fast data processing and real-time computational capabilities. By integrating advanced power management techniques, the RISC-V Core IP ensures energy efficiency without sacrificing performance, making it suitable for a wide range of electronic devices. Anticipating future computing needs, AheadComputing's RISC-V Core IP incorporates state-of-the-art features that support scalability and adaptability. These features ensure that the IP remains relevant as technology evolves, providing a solid foundation for developing next-generation computing solutions. Overall, it embodies AheadComputing’s commitment to innovation and performance excellence.
The Spiking Neural Processor T1 is designed as a highly efficient microcontroller that integrates neuromorphic intelligence closely with sensors. It employs a unique spiking neural network engine paired with a nimble RISC-V processor core, forming a cohesive unit for advanced data processing. With this setup, the T1 excels in delivering next-gen AI capabilities embedded directly at the sensor, operating within an exceptionally low power consumption range, ideal for battery-dependent and latency-sensitive applications. This processor marks a notable advancement in neuromorphic technology, allowing for real-time pattern recognition with minimal power draw. It supports various interfaces like QSPI, I2C, and UART, fitting into a compact 2.16mm x 3mm package, which facilitates easy integration into diverse electronic devices. Additionally, its architecture is designed to process different neural network models efficiently, from spiking to deep neural networks, providing versatility across applications. The T1 Evaluation Kit furthers this ease of adoption by enabling developers to use the Talamo SDK to create or deploy applications readily. It includes tools for performance profiling and supports numerous common sensors, making it a strong candidate for projects aiming to leverage low-power, intelligent processing capabilities. This innovative chip's ability to manage power efficiency with high-speed pattern processing makes it especially suitable for advanced sensing tasks found in wearables, smart home devices, and more.
The Chipchain C100 is a pioneering solution in IoT applications, providing a highly integrated single-chip design that focuses on low power consumption without compromising performance. Its design incorporates a powerful 32-bit RISC-V CPU which can reach speeds up to 1.5GHz. This processing power ensures efficient and capable computing for diverse IoT applications. This chip stands out with its comprehensive integrated features including embedded RAM and ROM, making it efficient in both processing and computing tasks. Additionally, the C100 comes with integrated Wi-Fi and multiple interfaces for transmission, broadening its application potential significantly. Other notable features of the C100 include an ADC, LDO, and a temperature sensor, enabling it to handle a wide array of IoT tasks more seamlessly. With considerations for security and stability, the Chipchain C100 facilitates easier and faster development in IoT applications, proving itself as a versatile component in smart devices like security systems, home automation products, and wearable technology.
The Maverick-2 Intelligent Compute Accelerator (ICA) by Next Silicon represents a transformative leap in high-performance compute architecture. It seamlessly integrates into HPC systems with a pioneering software-defined approach that dynamically optimizes hardware configurations based on real-time application demands. This enables high efficiency and unparalleled performance across diverse workloads including HPC, AI, and other data-intensive applications. Maverick-2 harnesses a 5nm process technology, utilizing HBM3E memory for enhanced data throughput and efficient energy usage.\n\nBuilt with developers in mind, Maverick-2 supports an array of programming languages such as C/C++, FORTRAN, and OpenMP without the necessity for proprietary stacks. This flexibility not only mitigates porting challenges but significantly reduces development time and costs. A distinguishing feature of Maverick-2 is its real-time telemetry capabilities that provide valuable insights into performance metrics, allowing for refined optimizations during execution.\n\nThe architecture supports versatile interfaces such as PCIe Gen 5 and offers configurations that accommodate complex workloads using either single or dual-die setups. Its intelligent algorithms autonomously identify computational bottlenecks to enhance throughput and scalability, thus future-proofing investments as computing demands evolve. Maverick-2's utility spans various sectors including life sciences, energy, and fintech, underlining its adaptability and high-performance capabilities.
The NMP-350 is an endpoint accelerator designed to deliver the lowest power and cost efficiency in its class. Ideal for applications such as driver authentication and health monitoring, it excels in automotive, AIoT/sensors, and wearable markets. The NMP-350 offers up to 1 TOPS performance with 1 MB of local memory, and is equipped with a RISC-V or Arm Cortex-M 32-bit CPU. It supports multiple use-cases, providing exceptional value for integrating AI capabilities into various devices. NMP-350's architectural design ensures optimal energy consumption, making it particularly suited to Industry 4.0 applications where predictive maintenance is crucial. Its compact nature allows for seamless integration into systems requiring minimal footprint yet substantial computational power. With support for multiple data inputs through AXI4 interfaces, this accelerator facilitates enhanced machine automation and intelligent data processing. This product is a testament to AiM Future's expertise in creating efficient AI solutions, providing the building blocks for smart devices that need to manage resources effectively. The combination of high performance with low energy requirements makes it a go-to choice for developers in the field of AI-enabled consumer technology.
Ncore Cache Coherent Interconnect is designed to tackle the multifaceted challenges in multicore SoC systems by introducing heterogeneous coherence and efficient cache management. This NoC IP optimizes performance by ensuring high throughput and reliable data transmission across multiple cores, making it indispensable for sophisticated computing tasks. Leveraging advanced cache coherency, Ncore maintains data integrity, crucial for maintaining system stability and efficiency in operations involving heavy computational loads. With its ISO26262 support, it caters to automotive and industrial applications requiring high reliability and safety standards. This interconnect technology pairs well with diverse processor architectures and supports an array of protocols, providing seamless integration into existing systems. It enables a coherent and connected multicore environment, enhancing the performance of high-stakes applications across various industry verticals, from automotive to advanced computing environments.
Syntacore’s SCR9 processor core stands out as a powerful force in handling high-performance computing tasks with its dual-issue out-of-order 12-stage pipeline. This core is engineered for environments that demand peak computational ability and robust pipeline execution, crucial for data-intense tasks such as AI and ML, enterprise applications, and network processing. The architecture is tailored to support extensive multicore and heterogeneous configurations, providing valuable tools for developers aiming to maximize workload efficiency and processing speed. The inclusion of a vector processing unit (VPU) underscores its capability to handle large datasets and complex calculations, while maintaining system integrity and coherence through its comprehensive cache management. With support for hypervisor functionalities and scalable Linux environments, the SCR9 continues to be a key strategic element in expanding the horizons of RISC-V-based applications. Syntacore’s extensive library of development resources further enriches the usability of this core, ensuring that its implementation remains smooth and effective across diverse technological landscapes.
Designed to cater to AI-specific needs, SEMIFIVE’s AI Inference Platform provides tailored solutions that seamlessly integrate advanced technologies to optimize performance and efficiency. This platform is engineered to handle the rigorous demands of AI workloads through a well-integrated approach combining hardware and software innovations matched with AI acceleration features. The platform supports scalable AI models, delivering exceptional processing capabilities for tasks involving neural network inference. With a focus on maximizing throughput and efficiency, it facilitates real-time processing and decision-making, which is crucial for applications such as machine learning and data analytics. SEMIFIVE’s platform simplifies AI implementation by providing an extensive suite of development tools and libraries that accelerate design cycles and enhance comprehensive system performance. The incorporation of state-of-the-art caching mechanisms and optimized data flow ensures the platform’s ability to handle large datasets efficiently.
NeuroMosAIc Studio serves as a comprehensive software platform that simplifies the process of developing and deploying AI models. Designed to optimize edge AI applications, this platform assists users through model conversion, mapping, and simulation, ensuring optimal use of resources and efficiency. It offers capabilities like network quantization and compression, allowing developers to push the limits in terms of performance while maintaining compact model sizes. The studio also supports precision adjustments, providing deep insights into hardware optimization, and aiding in the generation of precise outputs tailored to specific application needs. AiM Future's NeuroMosAIc Studio boosts the efficiency of training stages and quantization, ultimately facilitating the delivery of high-quality AI solutions for both existing and emerging technologies. It's an indispensable tool for those looking to enhance AI capabilities in embedded systems without compromising on power or performance.
Tailored for high efficiency, the NMP-550 accelerator advances performance in the fields of automotive, mobile, AR/VR, and more. Designed with versatility in mind, it finds applications in driver monitoring, video analytics, and security through its robust capabilities. Offering up to 6 TOPS of processing power, it includes up to 6 MB of local memory and a choice of RISC-V or Arm Cortex-M/A 32-bit CPU. In environments like drones, robotics, and medical devices, the NMP-550's enhanced computational skills allow for superior machine learning and AI functions. This is further supported by its ability to handle comprehensive data streams efficiently, making it ideal for tasks such as image analytics and fleet management. The NMP-550 exemplifies how AiM Future harnesses cutting-edge technology to develop powerful processors that meet contemporary demands for higher performance and integration into a multitude of smart technologies.
The SCR7 application core is at the forefront of performance and innovation, featuring a 12-stage dual-issue out-of-order pipeline with capabilities that support high-performance, Linux-capable application environments. This core is essential for scenarios demanding seamless cache coherency and support for complex operational tasks. Ideal for high-demand markets such as data centers, artificial intelligence, and mobile technologies, the SCR7 provides a robust and efficient solution that thrives under demanding conditions. It supports 64-bit SMP configurations up to 8 cores, effectively handling multi-threaded operations with superior data throughput capabilities. Syntacore enhances this core’s functionality through its comprehensive ecosystem of tools and support resources, ensuring developers can maximize the capabilities of this formidable hardware. The SCR7 stands as a testament to the scalability and adaptability intrinsic to the RISC-V architecture, reinforced by Syntacore's innovative approach to processor IP design.
The eSi-ADAS suite from EnSilica is a tailored collection of radar accelerator IPs designed to enhance automotive, drone, and UAV systems through advanced radar co-processing capabilities. This IP facilitates superior performance and enhanced situational awareness, crucial for applications requiring rapid and responsive decision-making. It merges cutting-edge radar technology with automotive standards, providing a robust platform for developing state-of-the-art driver assistance systems.\n\nThe suite’s radar co-processor engine is integral to improving radar system capabilities, ensuring that all signals are processed efficiently and accurately. This not only boosts the overall performance of radar systems but also aids in minimizing integration risks, streamlining the development process.\n\nFurthermore, eSi-ADAS supports various radar applications, enhancing safety and automation within the automotive sector. Its adaptability to UAV and drone designs also marks it as a versatile solution for unmanned systems, where responsiveness and precision are key.
Polar ID from Metalenz offers a cutting-edge face unlock solution, using advanced meta-optic technology to provide secure, high-resolution facial recognition capabilities. It captures the unique "polarization signature" of a human face, making it resistant to both 2D photos and sophisticated 3D masks. Polar ID operates efficiently in a variety of lighting conditions, from bright daylight to dark environments, ensuring its utility extends across all smartphone models without sacrificing security or user experience. This technology replaces complex structured light modules, incorporating a single near-infrared polarization camera and active illumination source. It significantly reduces costs and footprint, supporting a broad adoption across hundreds of millions of mobile devices. With its low price point and high performance, Polar ID elevates smartphone security, offering robust protection for digital transactions and identity verification. By enabling this on an embedded platform with compatibility for Qualcomm's Snapdragon processors, Metalenz ensures widespread applicability. The key advantage of Polar ID is its affordability and ease of integration, as it eliminates the need for larger, more intrusive notches in phone designs. Its sophisticated polarization sensing means secure authentication is possible even if the user wears sunglasses or masks. Polar ID sets a new benchmark in smartphone security by delivering convenience and enhanced protection, marking it as the first polarization sensor available for smartphones.
The RISCV SoC developed by Dyumnin Semiconductors is engineered with a 64-bit quad-core server-class RISCV CPU, aiming to bridge various application needs with an integrated, holistic system design. Each subsystem of this SoC, from AI/ML capabilities to automotive and multimedia functionalities, is constructed to deliver optimal performance and streamlined operations. Designed as a reference model, this SoC enables quick adaptation and deployment, significantly reducing the time-to-market for clients. The AI Accelerator subsystem enhances AI operations with its collaboration of a custom central processing unit, intertwined with a specialized tensor flow unit. In the multimedia domain, the SoC boasts integration capabilities for HDMI, Display Port, MIPI, and other advanced graphic and audio technologies, ensuring versatile application across various multimedia requirements. Memory handling is another strength of this SoC, with support for protocols ranging from DDR and MMC to more advanced interfaces like ONFI and SD/SDIO, ensuring seamless connectivity with a wide array of memory modules. Moreover, the communication subsystem encompasses a broad spectrum of connectivity protocols, including PCIe, Ethernet, USB, and SPI, crafting an all-rounded solution for modern communication challenges. The automotive subsystem, offering CAN and CAN-FD protocols, further extends its utility into automotive connectivity.
The Dynamic Neural Accelerator II (DNA-II) Architecture by EdgeCortix represents a leap in neural network processing capabilities, designed to yield exceptional parallelism and efficiency. It employs a runtime reconfigurable architecture that allows data paths to be reconfigured on-the-fly, maximizing parallelism and minimizing memory bandwidth usage on-chip. The DNA-II core can power AI applications across both convolutional and transformer networks, making it adaptable for a range of edge applications. Its scalable design, beginning from 1K MACs, facilitates flexible integration into SOC environments, while supporting a variety of target applications. It essentially serves as the powerhouse for the SAKURA-II AI Accelerator, enabling high-performance processing in compact form factors. Through the MERA software stack, DNA-II optimizes how network tasks are ordered and resources are allocated, providing precise scheduling and reducing inefficiencies found in other architectures. Additionally, the DNA-II features efficient energy consumption metrics, critical for edge implementations where performance must be balanced with power constraints.
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