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.
Akida Neural Processor IP by BrainChip serves as a pivotal technology asset for enhancing edge AI capabilities. This IP core is specifically designed to process neural network tasks with a focus on extreme efficiency and power management, making it an ideal choice for battery-powered and small-footprint devices. By utilizing neuromorphic principles, the Akida Neural Processor ensures that only the most relevant computations are prioritized, which translates to substantial energy savings while maintaining high processing speeds. This IP's compatibility with diverse data types and its ability to form multi-layer neural networks make it versatile for a wide range of industries including automotive, consumer electronics, and healthcare. Furthermore, its capability for on-device learning, without network dependency, contributes to improved device autonomy and security, making the Akida Neural Processor an integral component for next-gen intelligent systems. Companies adopting this IP can expect enhanced AI functionality with reduced development overheads, enabling quicker time-to-market for innovative AI solutions.
The Akida 2nd Generation continues BrainChip's legacy of low-power, high-efficiency AI processing at the edge. This iteration of the Akida platform introduces expanded support for various data precisions, including 8-, 4-, and 1-bit weights and activations, which enhance computational flexibility and efficiency. Its architecture is significantly optimized for both spatial and temporal data processing, serving applications that demand high precision and rapid response times such as robotics, advanced driver-assistance systems (ADAS), and consumer electronics. The Akida 2nd Generation's event-based processing model greatly reduces unnecessary operations, focusing on real-time event detection and response, which is vital for applications requiring immediate feedback. Furthermore, its sophisticated on-chip learning capabilities allow adaptation to new tasks with minimal data, fostering more robust AI models that can be personalized to specific use cases without extensive retraining. As industries continue to migrate towards AI-powered solutions, the Akida 2nd Generation provides a compelling proposition with its improved performance metrics and lower power consumption profile.
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.
Designed for high-performance applications, the Metis AIPU PCIe AI Accelerator Card by Axelera AI offers powerful AI processing capabilities in a PCIe card format. This card is equipped with the Metis AI Processing Unit, capable of delivering up to 214 TOPS, making it ideal for intensive AI tasks and vision applications that require substantial computational power. With support for the Voyager SDK, this card ensures seamless integration and rapid deployment of AI models, helping developers leverage existing infrastructures efficiently. It's tailored for applications that demand robust AI processing like high-resolution video analysis and real-time object detection, handling complex networks with ease. Highlighted for its performance in ResNet-50 processing, which it can execute at a rate of up to 3,200 frames per second, the PCIe AI Accelerator Card perfectly meets the needs of cutting-edge AI applications. The software stack enhances the developer experience, simplifying the scaling of AI workloads while maintaining cost-effectiveness and energy efficiency for enterprise-grade solutions.
MetaTF is BrainChip's toolkit aimed at optimizing and deploying machine learning models onto their proprietary Akida neuromorphic platform. This sophisticated toolset allows developers to convert existing models into sparse neural networks suited for Akida's efficient processing capabilities. MetaTF supports a seamless workflow from model conversion to deployment, simplifying the transition for developers aiming to leverage Akida's low-power, high-performance processing. The toolkit ensures that machine learning applications are optimized for edge deployment without compromising on speed or accuracy. This tool fosters an environment where AI models can be customized to meet specific application demands, delivering personalized and highly-innovative AI solutions. MetaTF's role is crucial in enabling developers to efficiently integrate complex neural networks into real-world devices, aiding in applications like smart city infrastructure, IoT devices, and industrial automation. By using MetaTF, companies can dramatically enhance the adaptability and responsiveness of their AI applications while maintaining stringent power efficiency standards.
Altek's AI Camera Module integrates sophisticated imaging technology with artificial intelligence, providing a powerful solution for high-definition visual capture and AI-based image processing. This module is tailored for applications where high precision and advanced analytic capabilities are required, such as in security systems and automotive technology. The module is equipped with a broad range of functionalities, including facial recognition, motion detection, and edge computing. It harnesses AI to process images in real-time, delivering insights and analytics that support decision-making processes in various environments. By combining AI with its imaging sensors, Altek enables next-generation visual applications that require minimal human intervention. Altek's AI Camera Module stands out for its high-degree of integration with IoT networks, allowing for seamless connectivity across devices. Its adaptability to different environments and conditions makes it a highly versatile tool. The module's design ensures durability and reliability, maintaining performance even under challenging conditions, thereby ensuring consistent and accurate image capture and processing.
Akida IP represents BrainChip's groundbreaking approach to neuromorphic AI processing. Inspired by the efficiencies of cognitive processing found in the human brain, Akida IP delivers real-time AI processing capabilities directly at the edge. Unlike traditional data-intensive architectures, it operates with significantly reduced power consumption. Akida IP's design supports multiple data formats and integrates seamlessly with other hardware platforms, making it flexible for a wide range of AI applications. Uniquely, it employs sparsity, focusing computation only on pertinent data, thereby minimizing unnecessary processing and conserving power. The ability to operate independently of cloud-driven data processes not only conserves energy but enhances data privacy and security by ensuring that sensitive data remains on the device. Additionally, Akida IP’s temporal event-based neural networks excel in tracking event patterns over time, providing invaluable benefits in sectors like autonomous vehicles where rapid decision-making is critical. Akida IP's remarkable integration capacity and its scalability from small, embedded systems to larger computing infrastructures make it a versatile choice for developers aiming to incorporate smart AI capabilities into various devices.
The Yitian 710 processor from T-Head represents a significant advancement in server chip technology, featuring an ARM-based architecture optimized for cloud applications. With its impressive multi-core design and high-speed memory access, this processor is engineered to handle intensive data processing tasks with efficiency and precision. It incorporates advanced fabrication techniques, offering high throughput and low latency to support next-generation cloud computing environments. Central to its architecture are 128 high-performance CPU cores utilizing the Armv9 structure, which facilitate superior computational capabilities. These cores are paired with substantial cache size and high-speed DDR5 memory interfaces, optimizing the processor's ability to manage massive workloads effectively. This attribute makes it an ideal choice for data centers looking to enhance processing speed and efficiency. In addition to its hardware prowess, the Yitian 710 is designed to deliver excellent energy efficiency. It boasts a sophisticated power management system that minimizes energy consumption without sacrificing performance, aligning with green computing trends. This combination of power, efficiency, and environmentally friendly design positions the Yitian 710 as a pivotal choice for enterprises propelling into the future of computing.
xcore.ai is a versatile and powerful processing platform designed for AIoT applications, delivering a balance of high performance and low power consumption. Crafted to bring AI processing capabilities to the edge, it integrates embedded AI, DSP, and advanced I/O functionalities, enabling quick and effective solutions for a variety of use cases. What sets xcore.ai apart is its cycle-accurate programmability and low-latency control, which improve the responsiveness and precision of the applications in which it is deployed. Tailored for smart environments, xcore.ai ensures robust and flexible computing power, suitable for consumer, industrial, and automotive markets. xcore.ai supports a wide range of functionalities, including voice and audio processing, making it ideal for developing smart interfaces such as voice-controlled devices. It also provides a framework for implementing complex algorithms and third-party applications, positioning it as a scalable solution for the growing demands of the connected world.
The Chimera GPNPU from Quadric is engineered to meet the diverse needs of modern AI applications, bridging the gap between traditional processing and advanced AI model requirements. It's a fully licensable processor, designed to deliver high AI inference performance while eliminating the complexity of traditional multi-core systems. The GPNPU boasts an exceptional ability to execute various AI models, including classical backbones, state-of-the-art transformers, and large language models, all within a single execution pipeline.\n\nOne of the core strengths of the Chimera GPNPU is its unified architecture that integrates matrix, vector, and scalar processing capabilities. This singular design approach allows developers to manage complex tasks such as AI inference and data-parallel processing without resorting to multiple tools or artificial partitioning between processors. Users can expect heightened productivity thanks to its modeless operation, which is fully programmable and efficiently executes C++ code alongside AI graph code.\n\nIn terms of versatility and application potential, the Chimera GPNPU is adaptable across different market segments. It's available in various configurations to suit specific performance needs, from single-core designs to multi-core clusters capable of delivering up to 864 TOPS. This scalability, combined with future-proof programmability, ensures that the Chimera GPNPU not only addresses current AI challenges but also accommodates the ever-evolving landscape of cognitive computing requirements.
The Metis AIPU M.2 Accelerator Module from Axelera AI is a cutting-edge solution designed for enhancing AI performance directly within edge devices. Engineered to fit the M.2 form factor, this module packs powerful AI processing capabilities into a compact and efficient design, suitable for space-constrained applications. It leverages the Metis AI Processing Unit to deliver high-speed inference directly at the edge, minimizing latency and maximizing data throughput. The module is optimized for a range of computer vision tasks, making it ideal for applications like multi-channel video analytics, quality inspection, and real-time people monitoring. With its advanced architecture, the AIPU module supports a wide array of neural networks and can handle up to 24 concurrent video streams, making it incredibly versatile for industries looking to implement AI-driven solutions across various sectors. Providing seamless compatibility with AI frameworks such as TensorFlow, PyTorch, and ONNX, the Metis AIPU integrates seamlessly with existing systems to streamline AI model deployment and optimization. This not only boosts productivity but also significantly reduces time-to-market for edge AI solutions. Axelera's comprehensive software support ensures that users can achieve maximum performance from their AI models while maintaining operational efficiency.
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 Talamo Software Development Kit (SDK) is a comprehensive toolkit designed to facilitate the development and deployment of advanced neuromorphic AI applications. Leveraging the familiar PyTorch environment, Talamo simplifies AI model creation and deployment, allowing developers to efficiently build spiking neural network models or adapt existing frameworks. The SDK integrates essential tools for compiling, training, and simulating AI models, providing users a complete environment to tailor their AI solutions without requiring extensive expertise in neuromorphic computing. One of Talamo's standout features is its seamless integration with the Spiking Neural Processor (SNP), offering an easy path from model creation to application deployment. The SDK's architecture simulator supports rapid validation and iteration, giving developers a valuable resource for refining their models. By enabling streamlined processes for building and optimizing applications, Talamo reduces development time and enhances the flexibility of AI deployment in edge scenarios. Talamo is designed to empower developers to utilize the full potential of brain-inspired AI, allowing the creation of end-to-end application pipelines. It supports building complex functions and neural networks through a plug-and-play model approach, minimizing the barriers to entry for deploying neuromorphic solutions. As an all-encompassing platform, Talamo paves the way for the efficient realization of sophisticated AI-driven applications, from inception to final implementation.
The SAKURA-II AI Accelerator represents a cutting-edge advancement in the field of generative AI, offering remarkable efficiency in a compact form factor. Engineered for rapid real-time inferencing, it excels in applications requiring low latency and robust performance in small, power-efficient silicon. This accelerator adeptly manages multi-billion parameter models, including Llama 2 and Stable Diffusion, under typical power requirements of 8W, catering to diverse applications from Vision to Language and Audio. Its core advantage lies in exceeding the AI compute utilization of other solutions, ensuring outstanding energy efficiency. The SAKURA-II further supports up to 32GB of DRAM, leveraging enhanced bandwidth for superior performance. Sparse computing techniques minimize memory footprint, while real-time data streaming and support for arbitrary activation functions elevate its functionality, enabling sophisticated applications in edge environments. This versatile AI accelerator not only enhances energy efficiency but also delivers robust memory management, supporting advanced precision for near-FP32 accuracy. Coupled with advanced power management, it suits a wide array of edge AI implementations, affirming its place as a leader in generative AI technologies at the edge.
The Jotunn8 AI Accelerator represents a pioneering approach in AI inference chip technology, designed to cater to the demanding needs of contemporary data centers. Its architecture is optimized for high-speed deployment of AI models, combining rapid data processing capabilities with cost-effectiveness and energy efficiency. By integrating features such as ultra-low latency and substantial throughput capacity, it supports real-time applications like chatbots and fraud detection that require immediate data processing and agile responses. The chip's impressive performance per watt metric ensures a lower operational cost, making it a viable option for scalable AI operations that demand both efficiency and sustainability. By reducing power consumption, Jotunn8 not only minimizes expenditure but also contributes to a reduced carbon footprint, aligning with the global move towards greener technology solutions. These attributes make Jotunn8 highly suitable for applications where energy considerations and environmental impact are paramount. Additionally, Jotunn8 offers flexibility in memory performance, allowing for the integration of complexity in AI models without compromising on speed or efficiency. The design emphasizes robustness in handling large-scale AI services, catering to the new challenges posed by expanding data needs and varied application environments. Jotunn8 is not simply about enhancing inference speed; it proposes a new baseline for scalable AI operations, making it a foundational element for future-proof AI infrastructure.
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 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 aiWare hardware neural processing unit (NPU) stands out as a state-of-the-art solution for automotive AI applications, bringing unmatched efficiency and performance. Designed specifically for inference tasks associated with automated driving systems, aiWare supports a wide array of AI workloads including CNNs, LSTMs, and RNNs, ensuring optimal operation across numerous applications.\n\naiWare is engineered to achieve industry-leading efficiency rates, boasting up to 98% efficiency on automotive neural networks. It operates across various performance requirements, from cost-sensitive L2 regulatory applications to advanced multi-sensor L3+ systems. The hardware platform is production-proven, already implemented in several products like Nextchip's APACHE series and enjoys strong industry partnerships.\n\nA key feature of aiWare is its scalability, capable of delivering up to 1024 TOPS with its multi-core architecture, and maintaining high efficiency in diverse AI tasks. The design allows for straightforward integration, facilitating early-stage performance evaluations and certifications with its deterministic operations and minimal host CPU intervention.\n\nA dedicated SDK, aiWare Studio, furthers the potential of the NPU by providing a suite of tools focused on neural network optimization, supporting developers in tuning their AI models with fine precision. Optimized for automotive-grade applications, aiWare's technology ensures seamless integration into systems requiring AEC-Q100 Grade 2 compliance, significantly enhancing the capabilities of automated driving applications from L2 through L4.
The 3D Imaging Chip by Altek Corporation is engineered to deliver exceptional depth sensing and precision in imaging applications. Built with advanced 3D sensing capabilities, it is designed for deployment in various environments that require detailed spatial awareness and object recognition. This chip is particularly beneficial for industries such as robotics and drones, where depth precision and object avoidance are critical. In addition to depth accuracy, this imaging chip offers robust integration with IoT platforms, promoting seamless interaction within smart ecosystems. It is equipped with features that support real-time data processing, allowing for immediate visualization and analysis of depth information. This enables enhanced AI-driven functionalities, ensuring that machines can interact with their environment more effectively. Altek's 3D Imaging Chip is distinguished by its low power consumption and adaptive design, which can be tailored to meet specific requirements of different tech sectors. It supports high-resolution data capture and efficient signal processing, providing clear and detailed visuals that enhance machine learning algorithms. Furthermore, its compatibility with a wide range of software tools makes it a versatile choice for developers looking to integrate advanced 3D imaging into their products.
The Hanguang 800 AI Accelerator by T-Head is designed to meet the needs of intensive machine learning workloads. Boasting superior performance, this AI accelerator leverages cutting-edge algorithms to enhance data processing capabilities, offering rapid speeds for AI tasks. It is particularly suited for deep learning applications that require high throughput and complex computation. Fitted with a highly efficient architecture, the Hanguang 800 speeds up machine learning model training and inference, enabling quicker deployments of AI solutions across industries. Its advanced design ensures compatibility with a wide range of machine learning frameworks, allowing for flexibility in AI application development and deployment. Energy efficiency is a key attribute of the Hanguang 800, incorporating modern power management features that reduce consumption without impacting performance. This makes it not only a high-performance option but also an environmentally friendly choice for businesses seeking to minimize their carbon footprint while optimizing AI processes.
The SiFive Intelligence X280 processor targets applications in machine learning and artificial intelligence, offering a high-performance, scalable architecture for emerging data workloads. As part of the Intelligence family, the X280 prioritizes a software-first methodology in processor design, addressing future ML and AI deployment needs, especially at the edge. This makes it particularly useful for scenarios requiring high computational power close to the data source. Central to its capabilities are scalable vector and matrix compute engines that can adapt to evolving workloads, thus future-proofing investments in AI infrastructure. With high-bandwidth bus interfaces and support for custom engine control, the X280 ensures seamless integration with varied system architectures, enhancing operational efficiency and throughput. By focusing on versatility and scalability, the X280 allows developers to deploy high-performance solutions without the typical constraints of more traditional platforms. It supports wide-ranging AI applications, from edge computing in IoT to advanced machine learning tasks, underpinning its role in modern and future-ready computing solutions.
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 is an ultra-low power AI processor designed for endpoint AI applications, offering extensive capabilities through an innovative architecture that merges a compact CMOS image sensor with an advanced AI microcontroller, the HX6538. This combination ensures the device remains always-on, consuming minimal power and making it ideal for battery-operated devices. It's built around an Arm Cortex-M55 CPU paired with an Ethos U55 NPU, fortified by a robust suite of sensor control interfaces and security features. WiseEye2 provides significant improvements over its predecessor with a 32-fold increase in processing capability and a 50% boost in energy efficiency, facilitating the execution of complex AI models with enhanced inference precision while retaining low power consumption. This enables intricate, always-on functionalities suitable for modern AI implementations. The solution is constructed to support a diverse array of smart applications beyond traditional boundaries, offering seamless integration and robust security for innovative AI endeavors. It encompasses neural network processing, multi-layer power management, and model optimization technology, making it a pivotal force in transforming how endpoint devices handle intelligent applications with minimal environmental impact.
The Spiking Neural Processor T1 is a neuromorphic microcontroller engineered for always-on sensor applications. It utilizes a spiking neural network engine alongside a RISC-V processor core, creating an ultra-efficient single-chip solution for real-time data processing. With its optimized power consumption, it enables next-generation artificial intelligence and signal processing in small, battery-operated devices. The T1 delivers advanced applications capabilities within a minimal power envelope, making it suitable for use in devices where power and latency are critical factors. The T1 includes a compact, multi-core RISC-V CPU paired with substantial on-chip SRAM, enabling fast and responsive processing of sensor data. By employing the remarkable abilities of spiking neural networks for pattern recognition, it ensures superior power performance on signal-processing tasks. The versatile processor can execute both SNNs and conventional processing tasks, supported by various standard interfaces, thus offering maximum flexibility to developers looking to implement AI features across different devices. Developers can quickly prototype and deploy solutions using the T1's development kit, which includes software for easy integration into existing systems and tools for accurate performance profiling. The development kit supports a variety of sensor interfaces, streamlining the creation of sophisticated sensor applications without the need for extensive power or size trade-offs.
The Polar ID system by Metalenz revolutionizes biometric security through its unique use of meta-optic technology. It captures the polarization signature of a human face, delivering a new level of security that can detect sophisticated 3D masks. Unlike traditional structured light technologies, which rely on complex dot-pattern projectors, Polar ID simplifies the module through a single, low-profile polarization camera that operates in near-infrared, ensuring functionality across varied lighting conditions and environments. Polar ID offers ultra-secure facial authentication capable of operating in both daylight and darkness, accommodating obstacles such as sunglasses and masks. This capability makes it particularly effective for smartphones and other consumer electronics, providing a more reliable and secure alternative to existing fingerprint and visual recognition technologies. By integrating smoothly into the most challenging smartphone designs, Polar ID minimizes the typical hardware footprint, making advanced biometric security accessible at a lower cost. This one-of-a-kind technology not only enhances digital security but also provides seamless user experiences by negating the need for multiple optical components. Its high resolution and accuracy ensure that performance is not compromised, safeguarding user authentication in real-time, even in adverse conditions. By advancing face unlock solutions, Polar ID stands as a future-ready answer to the rising demand for unobtrusive digital security in mainstream devices.
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 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 **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 Dynamic Neural Accelerator II (DNA-II) from EdgeCortix is an innovative architectural design that delivers high efficiency and exceptional parallelism for edge AI applications. Its unique runtime reconfigurable interconnects enable flexibility and scalable performance tailored to various AI workloads. Supporting both convolutional and transformer networks, DNA-II is integral to numerous system-on-chip (SoC) implementations, enhancing EdgeCortix's SAKURA-II AI Accelerators' performance and efficiency. A patent-backed data path reconfiguration technology allows DNA-II to optimize parallelism, minimize power consumption, and improve overall capability in handling complex neural networks. Additionally, it significantly reduces the reliance on on-chip memory bandwidth, enabling faster, more efficient task execution. DNA-II works seamlessly with the MERA software stack to ensure the optimal scheduling and allocation of computational resources, fostering enhanced AI model processing and efficient edge computing. Its adaptable architecture supports a wide spectrum of AI applications, making it a critical component of EdgeCortix's commitment to advancing edge AI technologies.
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.
Tyr AI Processor Family is engineered to bring unprecedented processing capabilities to Edge AI applications, where real-time, localized data processing is crucial. Unlike traditional cloud-based AI solutions, Edge AI facilitated by Tyr operates directly at the site of data generation, thereby minimizing latency and reducing the need for extensive data transfers to central data centers. This processor family stands out in its ability to empower devices to deliver instant insights, which is critical in time-sensitive operations like autonomous driving or industrial automation. The innovative design of the Tyr family ensures enhanced privacy and compliance, as data processing stays on the device, mitigating the risks associated with data exposure. By doing so, it supports stringent requirements for privacy while also reducing bandwidth utilization. This makes it particularly advantageous in settings like healthcare or environments with limited connectivity, where maintaining data integrity and efficiency is crucial. Designed for flexibility and sustainability, the Tyr AI processors are adept at balancing computing power with energy consumption, thus enabling the integration of multi-modal inputs and outputs efficiently. Their performance nears data center levels, yet they are built to consume significantly less energy, making them a cost-effective solution for implementing AI capabilities across various edge computing environments.
aiSim 5 represents a pivotal advancement in the simulation of automated driving systems, facilitating realistic and efficient validation of ADAS and autonomous driving components. Designed to exceed conventional expectations, aiSim 5 combines high-fidelity sensor and environment simulation with an AI-based digital twin concept to deliver unparalleled simulation accuracy and realism. It is the first simulator to be certified at ISO 26262 ASIL-D level, offering users the utmost industry trust.\n\nThe simulated environments are rooted in physics-based sensor data and cover a wide spectrum of operational design domains, including urban areas and highways. This ensures the simulation tests AD systems under diverse and challenging conditions, such as adverse weather events. aiSim 5's modular architecture supports easy integration with existing systems, leveraging open APIs to ensure seamless incorporation into various testing and continuous integration pipelines.\n\nNotably, aiSim 5 incorporates aiFab's domain randomization to create extensive synthetic data, mirroring real-world variances. This feature assists in identifying edge cases, allowing developers to test system responsiveness in rare but critical scenarios. By turning the spotlight on multi-sensor simulation and synthetic data generation, aiSim 5 acts as a powerful tool to accelerate the development lifecycle of ADAS and AD technologies, fostering innovation and development efficiency.\n\nThrough its intuitive graphical interface, aiSim 5 democratizes access to high-performance simulations, supporting operating systems like Microsoft Windows and Linux Ubuntu. This flexibility, coupled with the tool’s compatibility with numerous standards such as OpenSCENARIO and FMI, makes aiSim an essential component for automotive simulation projects striving for precision and agility.
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.
TT-Ascalon™ is a versatile RISC-V CPU core developed by Tenstorrent, emphasizing the utility of open standards to meet a diverse array of computing needs. Built to be highly configurable, TT-Ascalon™ allows for the inclusion of 2 to 8 cores per cluster complemented by a customizable L2 cache. This architecture caters to clients seeking a tailored processing solution without the limitations tied to proprietary systems. With support for CHI.E and AXI5-LITE interfaces, TT-Ascalon™ ensures robust connectivity while maintaining system integrity and performance density. Its security capabilities are premised on equivalent RISC-V primitives, ensuring a reliable and trusted environment for operations involving sensitive data. Tenstorrent’s engineering prowess, evident in TT-Ascalon™, has been shaped by experienced personnel from renowned tech giants. This IP is meant to align with various performance targets, suited for complex computational tasks that demand flexibility and efficiency in design.
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.
aiData serves as a comprehensive automated data pipeline tailored specifically for the development of ADAS and autonomous driving technologies. This solution optimizes various stages of MLOps, from data capturing to curation, significantly reducing the traditional manual workload required for assembling high-quality datasets. By leveraging cutting-edge technologies for data collection and annotation, aiData enhances the reliability and speed of deploying AD models, fostering a more efficient flow of data between developers and data scientists.\n\nOne of the standout features of aiData is its versioning system that ensures transparency and traceability throughout the data lifecycle. This system aids in curating datasets tailored for specific use cases via metadata enrichment and SQL querying, supporting seamless data management whether on-premise or cloud. Additionally, the aiData Recorder is engineered to produce high-quality datasets by enabling precise sensor calibration and synchronization, crucial for advanced driving applications.\n\nMoreover, the Auto Annotator component of aiData automates the traditionally labor-intensive process of data annotation, utilizing AI algorithms to produce annotations that meet high accuracy standards. This capability, combined with the aiData Metrics tool, allows for comprehensive validation of datasets, ensuring that they correctly reflect real-world conditions. Collectively, aiData empowers automotive developers to refine neural network algorithms and enhance detection software, accelerating the journey from MLOps to production.
The SiFive Performance family of processors is designed to offer top-tier performance and throughput across a range of sizes and power profiles. These cores provide highly efficient RISC-V scalar and vector computing capabilities, tailored for an optimal balance that delivers industry-leading results. With options for high-performance 64-bit out-of-order scalar engines and optional vector compute engines, the Performance series ensures customers get the maximum capabilities in computational power. Incorporating a robust architecture, these processors support extensive hardware capabilities, including full support for the RVA23 profile and an option for vector processing adjustments that maximizes computing efficiency. The SiFive Performance series has cores that cater to various needs, whether for general-purpose computing or applications requiring extensive parallel processing capabilities. SiFive's architecture allows for scalability and customization, bridging the gap between high-demand computational tasks and power efficiency. It is meticulously designed to meet the rigorous demands of modern and future computing applications, ensuring that both enterprise and consumer electronics can leverage the power of RISC-V computing. This makes it an ideal choice for developers seeking to push the boundaries of processing capabilities.
Tensix Neo is an AI-focused semiconductor solution from Tenstorrent that capitalizes on the robustness of RISC-V architecture. This IP is crafted to enhance the efficiency of both AI training and inference processes, making it a vital tool for entities needing scalable AI solutions without hefty power demands. With Tensix Neo, developers can rest assured of the silicon-proven reliability that backs its architecture, facilitating a smooth integration into existing AI platforms. The IP embraces the flexibility and customization needed for advanced AI workloads, optimizing resources and yielding results with high performance per watt. As the demand for adaptable AI solutions grows, Tensix Neo offers a future-proof platform that can accommodate rapid advancements and complex deployments in machine learning applications. By providing developers with tested and verified infrastructure, Tensix Neo stands as a benchmark in AI IP development.
Designed to accelerate the development of AI-driven solutions, the AI Inference Platform by SEMIFIVE offers a powerful infrastructure for deploying artificial intelligence applications quickly and efficiently. This platform encompasses an AI-focused architecture with silicon-proven IPs tailored specifically for machine learning tasks, providing a robust foundation for developers to build upon. The platform is equipped with high-performance processors optimized for AI workloads, including sophisticated neural processing units (NPUs) and memory interfaces that support large datasets and reduce latency in processing. It integrates seamlessly with existing tools and environments, minimizing the need for additional investments in infrastructure. Through strategic partnerships and an extensive library of pre-verified components, this platform reduces the complexity and time associated with AI application development. SEMIFIVE’s approach ensures end-users can focus on innovation rather than the underlying technology challenges, delivering faster time-to-market and enhanced performance for AI applications.
ELFIS2 is a cutting-edge sensor designed to meet the evolving requirements of space and scientific imaging applications. With its state-of-the-art architecture, the sensor is optimized for capturing high-resolution images in environments where precision and clarity are of utmost importance. It offers remarkable performance in capturing intricate details necessary for scientific exploration and research. This sensor is engineered with advanced features, including a high dynamic range and exceptional noise reduction capabilities, ensuring clarity and accuracy in every image captured. Such traits make it suitable for use in both terrestrial and extraterrestrial scientific endeavors, supporting studies that require detailed image analysis. ELFIS2 is perfectly suited for integration into scientific instruments, offering a robust solution that withstands the harsh conditions often encountered in space missions. Its adaptability and reliable performance make it an essential component for projects aiming to unlock new insights in scientific imaging, supporting endeavors from basic research to complex exploratory initiatives.
The Maverick-2 Intelligent Compute Accelerator (ICA) is a groundbreaking innovation by Next Silicon Ltd. This architecture introduces a novel software-defined approach that adapts in real-time to optimize computational tasks, breaking the traditional constraints of CPUs and GPUs. By dynamically learning and accelerating critical code segments, Maverick-2 ensures enhanced efficiency and performance efficiency for high-performance computing (HPC), artificial intelligence (AI), and vector databases. Designers have developed the Maverick-2 to support a wide range of common programming languages, including C/C++, FORTRAN, OpenMP, and Kokkos, facilitating an effortless porting process. This robust toolchain reduces time-intensive application porting, allowing for a significant cut in development time while maximizing scientific output and insights. Developers can enjoy seamless integration into their existing workflows without needing new proprietary software stacks. A standout feature of this intelligent architecture is its ability to adjust hardware configurations on-the-fly, optimizing power efficiency and overall performance. With an emphasis on sustainable innovation, the Maverick-2 offers a performance-per-watt advantage that exceeds traditional GPU and high-end CPU solutions by over fourfold, making it a cost-effective and environmentally friendly choice for modern data centers and research facilities.
The AON1100 offers a sophisticated AI solution for voice and sensor applications, marked by a remarkable power usage of less than 260μW during processing yet maintaining high levels of accuracy in environments with sub-0dB SNR. It is a leading option for always-on devices, providing effective solutions for contexts requiring constant machine listening ability.\n\nThis AI chip excels in processing real-world acoustic and sensor data efficiently, delivering up to 90% accuracy by employing advanced signal processing techniques. The AON1100's low power requirements make it an excellent choice for battery-operated devices, ensuring sustainable functionality through efficient power consumption over extended operational periods.\n\nThe scalability of the AON1100 allows it to be adapted for various applications, including smart homes and automotive settings. Its integration within broader AI platform strategies enhances intelligent data collection and contextual understanding capabilities, delivering transformative impacts on device interactivity and user experience.
The NoISA Processor is an innovative microprocessor designed by Hotwright Inc. to overcome the limitations of traditional instruction set architectures. Unlike standard processors, which rely on a fixed ALU, register file, and hardware controller, the NoISA Processor utilizes the Hotstate machine - an advanced microcoded algorithmic state machine. This technology allows for runtime reprogramming and flexibility, making it highly suitable for various applications where space, power efficiency, and adaptability are paramount. With the NoISA Processor, users can achieve significant performance improvements without the limitations imposed by fixed instruction sets. It's particularly advantageous in IoT and edge computing scenarios, offering enhanced efficiency compared to conventional softcore CPUs while maintaining lower energy consumption. Moreover, this processor is ideal for creating small, programmable state machines and Sysotlic arrays rapidly. Its unique architecture permits behavior modification through microcode, rather than altering the FPGA, thus offering unprecedented flexibility and power in adapting to specific technological needs.
The RISC-V CPU IP NS Class is specifically engineered for security-focused applications, including fintech mobile payments and IoT security. This architecture supports a variety of security protocols, making it ideal for systems that require robust data protection and secure transaction handling. It features a background in efficiently managing sensitive information, supporting comprehensive information security solutions with strong cryptographic capabilities. This IP is built with RISC-V's flexible extensions, ensuring files and communication streams maintain confidentiality and integrity in diverse operational scenarios. Robust by design, the NS Class caters to sectors such as IoT, where data protection is paramount, making it a trusted choice for developers seeking to enforce stringent security measures into their solutions. With options for extending functionality and increasing resilience through user-defined instructions, the NS Class remains adaptable for future security requirements.
SEMIFIVE's SoC Platform provides a comprehensive solution for rapid system-on-chip (SoC) development, tailoring these designs to various key applications. Leveraging purpose-built silicon-proven IPs and optimized design methodologies, it enables lower cost, minimized risk, and swift turnaround times. The platform employs a Domain-Specific Architecture, utilizing pre-configured and verified IP pools, making the integration and development process significantly faster and less complex. This platform is equipped with hardware/software prototypes that ensure customers can bring their ideas to fruition with less overhead and enhanced efficiency. It features technical highlights like the SiFive quad-core U74 RISC-V processor, LPDDR4x memory interfaces, and cutting-edge peripheral interfaces including PCIe Gen4, facilitating various applications ranging from AI inference to big data analytics and vision processing. Customers benefit from significantly reduced non-recurring engineering (NRE) costs and time-to-market durations that are up to 50% lower than the industry average. This framework maximizes design and verification component reusability, therefore reducing engineering risks. Its silicon-proven design ensures reliability and offers a variety of engagement models to cater to the unique needs of different projects.
Gyrus AI's Neural Network Accelerator is specifically crafted to enhance edge computing with its groundbreaking graph processing capabilities. This innovative solution achieves unparalleled efficiency with a performance of 30 trillion operations per second per Watt (TOPS/W). Such efficiency significantly enhances the speed of machine learning operations, minimizing the clock cycles required for tasks, which translates to a 10-30x reduction in clock-cycle count. As a low-power usage configuration, the Neural Network Accelerator ensures reduced energy consumption without compromising computational performance. Designed to offer seamless integration, this accelerator maximizes die area utilization over 80%, ensuring the efficient implementation of diverse model architectures. Its uniqueness lies in its software tools that complement the IP, facilitating the operation of neural networks on the IP with seamless ease. The Neural Network Accelerator is tailored to provide high performance without the trade-offs typically associated with increased power consumption, making it ideal for a variety of edge computing applications. The product serves as a critical enabler for enterprises seeking to implement sophisticated AI solutions at the edge, ensuring that their wide-ranging applications are both efficient and high-functioning. As edge devices increasingly drive innovation across industries, Gyrus AI's solution stands out for its dexterity in supporting complex model structures while conserving power, thereby catering to the modern demands of AI-driven operations.
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.
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.
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.
SEMIFIVE's AIoT Platform is engineered to drive the convergence of AI and the Internet of Things (IoT), facilitating smart, interconnected devices across various sectors. This platform is tailored for designing systems that require seamless integration of AI capabilities into IoT frameworks, offering a unique combination of flexibility and capability. Emphasizing energy efficiency and adaptability, the platform supports the development of edge-computing devices, smart home applications, robotics, and voice processing technologies. Featuring high-efficiency processors, it is designed to handle diverse data streams and perform real-time processing while maintaining low power consumption. Through its pre-integrated and verified components, the AIoT Platform simplifies the design process, allowing for rapid prototyping and deployment. SEMIFIVE empowers developers to create innovative solutions swiftly, adapting to the unique demands of IoT ecosystems and providing a robust foundation for future smart technologies.
Join the world's most advanced semiconductor IP marketplace!
It's free, and you'll get all the tools you need to discover IP, meet vendors and manage your IP workflow!
No credit card or payment details required.
Join the world's most advanced AI-powered semiconductor IP marketplace!
It's free, and you'll get all the tools you need to advertise and discover semiconductor IP, keep up-to-date with the latest semiconductor news and more!
Plus we'll send you our free weekly report on the semiconductor industry and the latest IP launches!