All IPs > Processor > Vision Processor
Vision processors are a specialized subset of semiconductor IPs designed to efficiently handle and process visual data. These processors are pivotal in applications that require intensive image analysis and computer vision capabilities, such as artificial intelligence, augmented reality, virtual reality, and autonomous systems. The primary purpose of vision processor IPs is to accelerate the performance of vision processing tasks while minimizing power consumption and maximizing throughput.
In the world of semiconductor IP, vision processors stand out due to their ability to integrate advanced functionalities such as object recognition, image stabilization, and real-time analytics. These processors often leverage parallel processing, machine learning algorithms, and specialized hardware accelerators to perform complex visual computations efficiently. As a result, products ranging from high-end smartphones to advanced driver-assistance systems (ADAS) and industrial robots benefit from improved visual understanding and processing capabilities.
The semiconductor IPs for vision processors can be found in a wide array of products. In consumer electronics, they enhance the capabilities of cameras, enabling features like face and gesture recognition. In the automotive industry, vision processors are crucial for delivering real-time data processing needed for safety systems and autonomous navigation. Additionally, in sectors such as healthcare and manufacturing, vision processor IPs facilitate advanced imaging and diagnostic tools, improving both precision and efficiency.
As technology advances, the demand for vision processor IPs continues to grow. Developers and designers seek IPs that offer scalable architectures and can be customized to meet specific application requirements. By providing enhanced performance and reducing development time, vision processor semiconductor IPs are integral to pushing the boundaries of what's possible with visual data processing and expanding the capabilities of next-generation products.
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 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 state-of-the-art neural processor that harnesses the power of brain-inspired computing principles. Engineered for ultra-low power consumption, it excels in real-time AI processing at the edge. The Akida architecture is characterized by its innovative use of sparsity, allowing it to focus computational resources on the most pertinent data while minimizing energy usage. This IP supports a variety of AI workloads, efficiently running both convolutional and fully-connected neural network layers. One of Akida's standout features is its on-chip learning capability. This functionality empowers devices to adapt and learn from new data with minimal need for cloud connectivity, enhancing both privacy and latency. Additionally, the Akida IP is highly configurable, offering extensive post-silicon flexibility, which ensures its adaptability across numerous applications such as vision processing, audio analysis, and sensor fusion. The platform's scalability is another notable advantage, allowing configurations from single to multiple neural nodes. This flexibility makes it a suitable choice for a wide range of AI applications, from small-scale consumer devices to larger industrial implementations. The successful integration of Akida IP in various products highlights its potential to revolutionize AI at the edge.
The Yitian 710 Processor represents T-Head Semiconductor's debut in Arm server chip development. It integrates cutting-edge architecture to deliver exceptional computing performance and efficiency. Designed for high-demand environments, this processor uses advanced Armv9 instruction set architecture, allowing for increased compatibility and robust performance metrics. With a design that maximizes throughput while minimizing power consumption, Yitian 710 is well-suited for cloud services and data-driven applications. The processor is engineered with a 2.5D packaging design, which enables enhanced performance through a dual-die structure. Its architecture includes 128 high-performance Armv9 CPU cores, each featuring a substantial cache and memory management capabilities, fostering smooth and efficient processing of large data volumes. This setup ensures high-speed data access and transfer, making it ideal for modern computational demands. The Yitian 710 Processor's I/O subsystem supports PCIe 5.0, providing substantial bandwidth to accommodate heavy data loads and improve interface interaction. This expansion capability makes the T-Head Yitian 710 Processor a versatile and scalable solution, designed to address the requirements of AI, big data analytics, and enterprise-level computing. Its power efficiency and support for high-frequency operations guarantee optimal performance in energy-conscious and high-load environments.
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 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 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.
The AX45MP is engineered as a high-performance processor that supports multicore architecture and advanced data processing capabilities, particularly suitable for applications requiring extensive computational efficiency. Powered by the AndesCore processor line, it capitalizes on a multicore symmetric multiprocessing framework, integrating up to eight cores with robust L2 cache management. The AX45MP incorporates advanced features such as vector processing capabilities and support for MemBoost technology to maximize data throughput. It caters to high-demand applications including machine learning, digital signal processing, and complex algorithmic computations, ensuring data coherence and efficient power usage.
The SiFive Intelligence X280 is a high-performance CPU core tailored for advanced AI and ML workloads, featuring sophisticated vector and matrix compute capabilities. It offers developers a vast toolkit for crafting efficient AI solutions that can be deployed at the edge, thanks to a focus on providing both high performance and scalability. The X280’s architecture allows for the integration of custom accelerator engines, making it highly adaptable to shifting demands in AI technology. Boasting advanced vector compute engines, the X280 is designed to handle large datasets efficiently, ideal for inference tasks and model training. This processor stands out with its high bandwidth interconnects, facilitating seamless data flow and control across custom computing engines integrated using RISC-V custom instructions. Its capabilities mark it as a versatile choice for complex machine learning applications spanning various industry segments. The SiFive Intelligence X280 supports a broad range of tools and frameworks designed to simplify deployment and integration. By using a RISC-V architecture, it promotes open innovation and reduces dependency on traditional proprietary models. This freedom translates into increased optimization opportunities, enabling rapid iteration and development cycles critical for maintaining a competitive edge in AI technology.
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 Hanguang 800 AI Accelerator from T-Head Semiconductor delivers powerful capabilities aimed at boosting artificial intelligence applications across a range of industries. This accelerator is designed to manage complex neural network computations, facilitating real-time AI processing that meets today’s evolving technological demands. It is ideally suited for tasks such as machine learning model training and inferencing, providing significant improvements in both speed and efficiency. The Hanguang 800 features a sophisticated architecture that harnesses multiple processing units, optimized specifically for neural network computations. This structure allows for parallel processing, significantly accelerating data handling and computation tasks crucial to AI applications. This ability to rapidly process vast amounts of information makes it a preferred choice for data centers and enterprises specializing in AI technologies. Built to integrate smoothly with existing infrastructures, the Hanguang 800 accommodates various AI frameworks, enhancing development flexibility. Its robust design ensures high throughput and minimal latency in AI operations, making it highly suitable for intensive AI workloads. It provides an efficient, scalable solution for enterprises looking to enhance their AI capabilities and maintain a competitive edge in the dynamic tech landscape.
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.
The WiseEye2 AI Solution by Himax is a low-power AI processing solution tailored for IoT devices. It integrates sensor fusion technology, making it ideal for applications in smart homes, intelligent security systems, and consumer electronics. This solution is designed to handle complex AI algorithms at minimal power consumption, enabling efficient and advanced functionalities in smart applications.
Altek's 3D Imaging Chip is a breakthrough in the field of vision technology. Designed with an emphasis on depth perception, it enhances the accuracy of 3D scene capturing, making it ideal for applications requiring precise distance gauging such as autonomous vehicles and drones. The chip integrates seamlessly within complex systems, boasting superior recognition accuracy that ensures reliable and robust performance. Building upon years of expertise in 3D imaging, this chip supports multiple 3D modes, offering flexible solutions for devices from surveillance robots to delivery mechanisms. It facilitates medium-to-long-range detection needs thanks to its refined depth sensing capabilities. Altek's approach ensures a comprehensive package from modular design to chip production, creating a cohesive system that marries both hardware and software effectively. Deployed within various market segments, it delivers adaptable image solutions with dynamic design agility. Its imaging prowess is further enhanced by state-of-the-art algorithms that refine image quality and facilitate facial detection and recognition, thereby expanding its utility across diverse domains.
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 **Ceva-SensPro DSP family** unites scalar processing units and vector processing units under an 8-way VLIW architecture. The family incorporates advanced control features such as a branch target buffer and a loop buffer to speed up execution and reduce power. There are six family members, each with a different array of MACs, targeted at different application areas and performance points. These range from the Ceva-SP100, providing 128 8-bit integer or 32 16-bit integer MACs at 0.2 TOPS performance for compact applications such as vision processing in wearables and mobile devices; to the Ceva-SP1000, with 1024 8-bit or 256 16-bit MACs reaching 2 TOPS for demanding applications such as automotive, robotics, and surveillance. Two of the family members, the Ceva-SPF2 and Ceva-SPF4, employ 32 or 64 32-bit floating-point MACs, respectively, for applications in electric-vehicle power-train control and battery management. These two members are supported by libraries for Eigen Linear Algebra, MATLAB vector operations, and the TVM graph compiler. Highly configurable, the vector processing units in all family members can add domain-specific instructions for such areas as vision processing, Radar, or simultaneous localization and mapping (SLAM) for robotics. Integer family members can also add optional floating-point capabilities. All family members have independent instruction and data memory subsystems and a Ceva-Connect queue manager for AXI-attached accelerators or coprocessors. The Ceva-SensPro2 family is programmable in C/C++ as well as in Halide and Open MP, and supported by an Eclipse-based development environment, extensive libraries spanning a wide range of applications, and the Ceva-NeuPro Studio AI development environment. [**Learn more about Ceva-SensPro2 solution>**](https://www.ceva-ip.com/product/ceva-senspro2/?utm_source=silicon_hub&utm_medium=ip_listing&utm_campaign=ceva_senspro2_page)
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 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.
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 RayCore MC is a revolutionary real-time path and ray-tracing GPU designed to enhance rendering with minimal power consumption. This GPU IP is tailored for real-time applications, offering a rich graphical experience without compromising on speed or efficiency. By utilizing advanced ray-tracing capabilities, RayCore MC provides stunning visual effects and lifelike animations, setting a high standard for quality in digital graphics. Engineered for scalability and performance, RayCore MC stands out in the crowded field of GPU technologies by delivering seamless, low-latency graphics. It is particularly suited for applications in gaming, virtual reality, and the burgeoning metaverse, where realistic rendering is paramount. The architecture supports efficient data management, ensuring that even the most complex visual tasks are handled with ease. RayCore MC's architecture supports a wide array of applications beyond entertainment, making it a vital tool in areas such as autonomous vehicles and data-driven industries. Its blend of power efficiency and graphical prowess ensures that developers can rely on RayCore MC for cutting-edge, resource-light graphic solutions.
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.
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 AI Inference Platform is designed to optimize the deployment of AI workloads across various applications. Built with cutting-edge IP and advanced design methodologies, it ensures cost efficiency and minimizes the risks associated with product development. The platform is engineered to capitalize on domain-specific architectures, offering a reduction in time and expense during the SoC creation process. This platform boasts pre-configured and robust components, refined through silicon-proven practices, delivering rapid hardware and software integration. Its flexible design is capable of addressing diverse AI applications, enhancing performance with lower power consumption and elevated reliability. By utilizing SEMIFIVE’s AI Inference Platform, developers can accelerate their projects with reduced time to market and enhanced design reusability. This is achieved through SEMIFIVE’s commitment to validating each component rigorously, ensuring high performance in AI-driven environments.
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.
AON1100 marks a significant leap in edge AI processing for voice and sensor operations. Meticulously engineered for energy efficiency, this chip operates on less than 260µW while achieving over 90% accuracy even in low signal-to-noise environments. It is perfect for always-on gadgets demanding constant reliability and precision, especially under challenging conditions.
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.
aiData is designed to streamline the data pipeline for developing models for Advanced Driver-Assistance Systems and Automated Driving solutions. This automated system provides a comprehensive method of managing and processing data, from collection through curation, annotation, and validation. It significantly reduces the time required for data processing by automating many labor-intensive tasks, enabling teams to focus more on development rather than data preparation. The aiData platform includes sophisticated tools for recording, managing, and annotating data, ensuring accuracy and traceability through all stages of the MLOps workflow. It supports the creation of high-quality training datasets, essential for developing reliable and effective AI models. The platform's capabilities extend beyond basic data processing by offering advanced features such as versioning and metrics analysis, allowing users to track data changes over time and evaluate dataset quality before training. The aiData Recorder feature ensures high-quality data collection tailored to diverse sensor configurations, while the Auto Annotator quickly processes data for a variety of objects using AI algorithms, delivering superior precision levels. These features are complemented by aiData Metrics, which provide valuable insights into dataset completeness and adequacy in covering expected operational domains. With seamless on-premise or cloud deployment options, aiData empowers global automotive teams to collaborate efficiently, offering all necessary tools for a complete data management lifecycle. Its integration versatility supports a wide array of applications, helping improve the speed and effectiveness of deploying ADAS models.
The ELFIS2 Image Sensor is a sophisticated development from Caeleste tailored for advanced imaging applications. It is designed to offer unparalleled image fidelity across a plethora of environments, making it an indispensable tool for both scientific and space missions. This image sensor excels in capturing high contrast and high detail images, even under challenging conditions such as low light or rapidly changing brightness.\n\nELFIS2 features state-of-the-art image processing capabilities, combined with robust construction to withstand the rigors of space missions. The sensor is optimized to operate efficiently with minimal power consumption while delivering high-resolution images, ensuring that mission data is both accurate and reliable. The sensor's design also facilitates ease of integration into complex systems, providing a seamless fit for advanced imaging needs.\n\nCaeleste's expertise ensures that the ELFIS2 sensor is equipped with the latest in sensor technology, making it suitable for a variety of applications ranging from astronomy to industrial monitoring. Whether deployed in outer space or earthbound observation platforms, the ELFIS2 Image Sensor proves to be a remarkable blend of technology and craftsmanship.
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.
Specially engineered for the automotive industry, the NA Class IP by Nuclei complies with the stringent ISO26262 functional safety standards. This processor is crafted to handle complex automotive applications, offering flexibility and rigorous safety protocols necessary for mission-critical transportation technologies. Incorporating a range of functional safety features, the NA Class IP is equipped to ensure not only performance but also reliability and safety in high-stakes vehicular environments.
Tachyum's Prodigy Universal Processor marks a significant milestone as it combines the functionalities of Central Processing Units (CPUs), General-Purpose Graphics Processing Units (GPGPUs), and Tensor Processing Units (TPUs) into a single cohesive architecture. This groundbreaking design is tailored to meet the escalating demands of artificial intelligence, high-performance computing, and hyperscale data centers by offering unparalleled performance, energy efficiency, and high utilization rates. The Prodigy processor not only tackles common data center challenges like elevated power consumption and stagnating processor performance but also offers a robust solution to enhance server utilization and reduce the carbon footprint of massive computational installations. Notably, it thrives on a simplified programming model grounded in coherent multiprocessor architecture, thereby enabling seamless execution of an array of AI disciplines like Explainable AI, Bio AI, and deep machine learning within a single hardware platform.
The NS Class is Nuclei's crucial offering for applications prioritizing security and fintech solutions. This RISC-V CPU IP securely manages IoT environments with its highly customizable and secure architecture. Equipped to support advanced security protocols and functional safety features, the NS Class is particularly suited for payment systems and other fintech applications, ensuring robust protection and reliable operations. Its design follows the RISC-V standards and is accompanied by customizable configuration options tailored to meet specific security requirements.
The SiFive Performance series represents a leap forward in computing efficiency, featuring RISC-V processors designed for peak performance and high throughput across various applications. These 64-bit out-of-order cores come equipped with up to 256-bit vectors, optimizing them for data center workloads, web services, multimedia processing, and consumer electronics like smart devices. The Performance series balances cutting-edge energy efficiency with robust core capabilities, making it suited for AI workloads while minimizing power and spatial requirements. The SiFive Performance family’s design includes flexible core configurations that empower users to mix and match performance levels according to their specific needs. This approach results in streamlined and powerful processors suitable for a broad spectrum of applications, ranging from mobile devices to complex data center infrastructure. SiFive’s utilization of vector engines enhances AI applications, offering significant computational capability without imposing additional hardware demands. With the ability to expand up to 256 cores and integrate vector computing capabilities, SiFive's Performance series provides a high degree of scalability. Users benefit from enhanced performance density, allowing for the development of next-generation applications that require high levels of processing power within limited physical constraints. This range is an excellent choice for developers looking for efficient, scalable solutions tailored to diverse operational requirements.
The eSi-3264 stands out with its support for both 32/64-bit operations, including 64-bit fixed and floating-point SIMD (Single Instruction Multiple Data) DSP extensions. Engineered for applications mandating DSP functionality, it does so with minimal silicon footprint. Its comprehensive instruction set includes specialized commands for various tasks, bolstering its practicality across multiple sectors.
The Trifecta-GPU series by RADX is a flagship family of COTS PXIe/CPCIe GPU modules that leverage the power of NVIDIA RTX A2000 Embedded GPUs. Aimed at high-complexity applications in modular test and measurement (T&M) and electronic warfare (EW), these modules provide robust compute acceleration. With peak performance metrics reaching 8.3 FP32 TFLOPS, the Trifecta-GPU modules are engineered to handle demanding tasks in signal processing and machine/deep learning inference. These products are designed for compatibility with MATLAB, Python, and C/C++, ensuring ease of integration across different programming environments. Additionally, the Trifecta-GPU configuration supports PCIe Gen 4 x8 interfaces alongside miniDP outputs, catering to high-resolution multi-monitor setups.
The NX Class RISC-V CPU IP by Nuclei is characterized by its 64-bit architecture, making it a robust choice for storage, AR/VR, and AI applications. This processing unit is designed to accommodate high data throughput and demanding computational tasks. By leveraging advanced capabilities, such as virtual memory and enhanced processing power, the NX Class facilitates cutting-edge technological applications and is adaptable for integration into a vast array of high-performance systems.
The Neural Network Accelerator by Gyrus AI is an advanced compute solution specially optimized for neural network applications. It features native graph processing capabilities that significantly enhance the computational efficiency of AI models. This IP component supports high-speed operations with 30 TOPS/W, offering exceptional performance that significantly reduces the clock cycles typically required by other systems.\n\nMoreover, the architecture is designed to consume 10-20 times less power, benefitting from a low-memory usage configuration. This efficiency is further highlighted by the IP’s ability to achieve an 80% utilization rate across various model structures, which translates into significant reductions in die area requirements up to 8 to 10 times smaller than conventional designs.\n\nGyrus AI’s Neural Network Accelerator also supports seamless integration of software tools tailored to run neural networks on the platform, making it a practical choice for edge computing applications. It not only supports large-scale AI computations but also minimizes power consumption and space constraints, making it ideal for high-performance environments.
The NI Class RISC-V CPU IP caters to communication, video processing, and AI applications, providing a balanced architecture for intensive data handling and processing capabilities. With a focus on high efficiency and flexibility, this processor supports advanced data crunching and networking applications, ensuring that systems run smoothly and efficiently even when managing complex algorithms. The NI Class upholds Nuclei's commitment to providing versatile solutions in the evolving tech landscape.
The Origin E1 processors are designed specifically for applications requiring constant vigilance with minimal power usage, including home appliances and smartphone features. It excels at power efficiency, ensuring that always-sensing cameras operate effectively with low power consumption, keeping visual data processing secure without needing external memory. Expedera’s LittleNPU architecture enhances processing efficiency by executing multiple layers in parallel, providing both sustained performance and reduced latency.
The Vega eFPGA is a flexible programmable solution crafted to enhance SoC designs with substantial ease and efficiency. This IP is designed to offer multiple advantages such as increased performance, reduced costs, secure IP handling, and ease of integration. The Vega eFPGA boasts a versatile architecture allowing for tailored configurations to suit varying application requirements. This IP includes configurable tiles like CLB (Configurable Logic Blocks), BRAM (Block RAM), and DSP (Digital Signal Processing) units. The CLB part includes eight 6-input Lookup Tables that provide dual outputs, and also an optional configuration with a fast adder having a carry chain. The BRAM supports 36Kb dual-port memory and offers flexibility for different configurations, while the DSP component is designed for complex arithmetic functions with its 18x20 multipliers and a wide 64-bit accumulator. Focused on allowing easy system design and acceleration, Vega eFPGA ensures seamless integration and verification into any SoC design. It is backed by a robust EDA toolset and features that allow significant customization, making it adaptable to any semiconductor fabrication process. This flexibility and technological robustness places the Vega eFPGA as a standout choice for developing innovative and complex programmable logic solutions.
CTAccel's Image Processor for AWS offers a powerful image processing acceleration solution as part of Amazon's cloud infrastructure. This FPGA-based processor is available as an Amazon Machine Image (AMI) and enables customers to significantly enhance their image processing capabilities within the cloud environment. The AWS-based accelerator provides a remarkable tenfold increase in image processing throughput and similar reductions in computational latency, positively impacting Total Cost of Ownership (TCO) by reducing infrastructure needs and improving operational efficiency. These enhancements are crucial for applications requiring intensive image analysis and processing. Moreover, the processor supports a variety of image enhancement functions such as JPEG thumbnail generation and color adjustments, making it suitable for diverse cloud-based processing scenarios. Its integration within the AWS ecosystem ensures that users can easily deploy and manage these advanced processing capabilities across various imaging workflows with minimal disruption.
The SoC Platform offered by SEMIFIVE is a versatile solution that accelerates the design and development of System-on-Chip (SoC) products. Leveraging domain-specific architecture and a rich pool of silicon-proven IP, this platform is crafted for key applications, ensuring reduced costs and risks while speeding up time-to-market. It provides a pre-configured and verified IP ecosystem that is ready for immediate hardware and software bring-up. One of the platform's standout features is its flexible architecture model, which supports a broad range of applications from AI inference to IoT and high-performance computing. This modular approach enables users to efficiently integrate their unique requirements with a lower non-recurring engineering (NRE) cost, maximizing component reusability and minimizing engineering risks. Additionally, the SoC platform facilitates rapid prototyping by offering a pre-selected and tested range of platform IP pools. These components are silicon-proven, ensuring seamless integration and reliability. With SEMIFIVE’s extensive support and comprehensive solutions, customers can confidently bring their innovative ideas to silicon, backed by state-of-the-art technology and industry expertise.
The memBrain™ technology is pioneering advancements in neuromorphic computing by optimizing neural network inference at the edge. By incorporating analog compute-in-memory techniques, memBrain™ efficiently handles deep neural networks' substantial Multiply-Accumulate (MAC) operations, pivotal for AI applications like video and voice recognition. This integration significantly enhances system performance by reducing system bus latencies and power consumption—achieving up to 20-fold power savings compared to conventional digital DSP methods.\n\nUtilizing SuperFlash® technology, memBrain™ stores significant synaptic weights within the floating gate, mitigating the need for off-chip storage and streamlining processing capabilities. The result is a reduction in both cost and system complexity, making advanced AI inferencing capabilities widely accessible. As AI applications evolve to require more efficient storage management, memBrain™ stands out as a solution that economizes power without compromising on performance.\n\nmemBrain™ is particularly influential in scenarios requiring efficient weight storage and MAC operations, such as large-scale neural systems. By employing a tile-based architecture, it supports numerous configurations tailored to specific application needs, ensuring scalability and adaptability in diverse AI models, from edge devices to broader AI systems. This adaptability positions memBrain™ as a forefront technology for edge AI innovations, offering robust solutions across various sectors from industrial to consumer applications.
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.
The AIoT Platform from SEMIFIVE merges artificial intelligence with Internet of Things applications, providing a robust infrastructure for the next generation of smart devices. This platform capitalizes on the synergy between AI and IoT, designed to deliver high efficiency and seamless integration for diverse IoT ecosystems. Utilizing the latest process technologies and silicon-proven IPs, the AIoT Platform enables rapid development cycles. It supports a wide range of AIoT applications, enhancing functionalities such as edge computing, smart home technologies, and advanced IoT networks. Developers opting for SEMIFIVE's AIoT Platform benefit from a scalable and flexible architecture, allowing for customizable implementations tailored to specific application needs. The platform ensures that all components work harmoniously to optimize performance while maintaining energy efficiency, catering to the growing demands of interconnected smart devices.
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