All IPs > Processor > IoT Processor
The "IoT Processor" category in our Silicon Hub catalog features a range of semiconductor IPs specifically engineered for the Internet of Things (IoT) landscape. These IPs play a critical role in enabling smart connectivity, control, and data processing in IoT devices. Leveraging cutting-edge technology, IoT processors are designed to meet the unique demands of interconnected smart devices, balancing the need for powerful performance with energy efficiency and seamless connectivity.
IoT processors are central to a wide array of applications, from smart homes and industrial IoT to wearables and smart cities. In smart homes, IoT processors enable devices to interact seamlessly, allowing for automated lighting, climate control, and security systems. In industrial settings, they facilitate real-time monitoring and analytics, improving operational efficiency and safety. The compact and efficient designs of these processors also make them ideal for wearables, where power consumption and size are critical factors.
The semiconductor IPs available in this category support a variety of architectures and computing needs, providing flexibility in design and application. They incorporate advanced features such as multi-core processing, integrated connectivity solutions like Wi-Fi and Bluetooth, and robust security protocols to protect sensitive data. These processors are optimized to handle the challenges of IoT environments, offering low latency and the ability to process data locally, reducing the dependency on cloud computing and enhancing response times.
Furthermore, the "IoT Processor" category emphasizes sustainability by offering IPs that reduce energy consumption while maintaining high performance levels. This makes them vital components in developing sustainable IoT solutions that are both environmentally friendly and economically viable. As IoT technology continues to evolve, the processors in this category will enable innovation, drive market growth, and fulfill the increasing demands of a connected world.
The Akida 2nd Generation is an evolution of BrainChip's innovative neural processor technology. It builds upon its predecessor's strengths by delivering even greater efficiency and a broader range of applications. The processor maintains an event-based architecture that optimizes performance and power consumption, providing rapid response times suitable for edge AI applications that prioritize speed and privacy.\n\nThis next-generation processor enhances accuracy with support for 8-bit quantization, which allows for finer grained processing capabilities and more robust AI model implementations. Furthermore, it offers extensive scalability, supporting configurations from a few nodes for low-power needs to many nodes for handling more complex cognitive tasks. As with the previous version, its architecture is inherently cloud-independent, enabling inference and learning directly on the device.\n\nAkida 2nd Generation continues to push the boundaries of AI processing at the edge by offering enhanced processing capabilities, making it ideal for applications demanding high accuracy and efficiency, such as automotive safety systems, consumer electronics, and industrial monitoring.
The AI Camera Module by Altek Corporation exemplifies cutting-edge image capture technology, integrating both hardware and software to deliver high-quality, intelligent imaging solutions. This module is built on robust AI frameworks allowing it to adapt and optimize image processing based on specific application needs. It finds use in areas where high-resolution and real-time processing are essential, such as security systems and automotive industries.<br/><br/>Equipped with versatile imaging sensors, the AI Camera Module ensures excellent picture quality even in challenging lighting conditions, thanks to its AI-driven image enhancement algorithms. It supports edge computing, which reduces latency and enhances the speed of image analysis, thus providing timely insights and data processing right on the device itself.<br/><br/>This camera module stands out for its interoperability with IoT devices, paving the way for a more interconnected and intelligent ecosystem. Its advanced features such as facial detection, motion tracking, and object recognition empower users across various domains, from consumer electronics to industrial solutions, making it an indispensable tool for modern digital infrastructures.
The NMP-750 is a high-performance accelerator designed for edge computing, particularly suited for automotive, AR/VR, and telecommunications sectors. It boasts an impressive capacity of up to 16 TOPS and 16 MB local memory, powered by a RISC-V or Arm Cortex-R/A 32-bit CPU. The three AXI4 interfaces ensure seamless data transfer and processing. This advanced accelerator supports multifaceted applications such as mobility control, building automation, and multi-camera processing. It's designed to cope with the rigorous demands of modern digital and autonomous systems, offering substantial processing power and efficiency for intensive computational tasks. The NMP-750's ability to integrate into smart systems and manage spectral efficiency makes it crucial for communications and smart infrastructure management. It helps streamline operations, maintain effective energy management, and facilitate sophisticated AI-driven automation, ensuring that even the most complex data flows are handled efficiently.
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 A25 processor model is a versatile CPU suitable for a variety of embedded applications. With its 5-stage pipeline and 32/64-bit architecture, it delivers high performance even with a low gate count, which translates to efficiency in power-sensitive environments. The A25 is equipped with Andes Custom Extensions that enable tailored instruction sets for specific application accelerations. Supporting robust high-frequency operations, this model shines in its ability to manage data prefetching and cache coherence in multicore setups, making it adept at handling complex processing tasks within constrained spaces.
The Chimera GPNPU from Quadric is designed as a general-purpose neural processing unit intended to meet a broad range of demands in machine learning inference applications. It is engineered to perform both matrix and vector operations along with scalar code within a single execution pipeline, which offers significant flexibility and efficiency across various computational tasks. This product achieves up to 864 Tera Operations per Second (TOPs), making it suitable for intensive applications including automotive safety systems. Notably, the GPNPU simplifies system-on-chip (SoC) hardware integration by consolidating hardware functions into one processor core. This unification reduces complexity in system design tasks, enhances memory usage profiling, and optimizes power consumption when compared to systems involving multiple heterogeneous cores such as NPUs and DSPs. Additionally, its single-core setup enables developers to efficiently compile and execute diverse workloads, improving performance tuning and reducing development time. The architecture of the Chimera GPNPU supports state-of-the-art models with its Forward Programming Interface that facilitates easy adaptation to changes, allowing support for new network models and neural network operators. It’s an ideal solution for products requiring a mix of traditional digital signal processing and AI inference like radar and lidar signal processing, showcasing a rare blend of programming simplicity and long-term flexibility. This capability future-proofs devices, expanding their lifespan significantly in a rapidly evolving tech landscape.
The KL520 was Kneron's first foray into AI SoCs, characterized by its small size and energy efficiency. This chip integrates a dual ARM Cortex M4 CPU architecture, which can function both as a host processor and as a supportive AI co-processor for diverse edge devices. Ideal for smart devices such as door locks and cameras, it is compatible with various 3D sensor technologies, offering a balance of compact design and high performance. As a result, this SoC has been adopted by multiple products in the smart home and security sectors.
The RV12 RISC-V Processor from Roa Logic is a highly versatile CPU designed for embedded applications. It complies with the RV32I and RV64I specifications of the RISC-V instruction set, supporting single-core configurations. The RV12 processor is renowned for its configurability, allowing it to be tailored to specific application requirements. It implements a Harvard architecture, which enables concurrent access to both instruction and data memory, optimizing performance and efficiency. Roa Logic's RV12 processor is part of their broader portfolio of 32/64-bit CPU solutions that leverage the open-source RISC-V instruction set. This architecture is favored for its simplicity and scalability, making it ideal for various embedded systems. The processor is equipped with an optimizing feature set that enhances its processing capabilities, ensuring it meets the rigorous demands of modern applications. Incorporating the RV12 processor into projects is streamlined thanks to its comprehensive support documentation and available test benches. These resources facilitate smooth integration into larger systems, providing developers with a reliable foundation for building advanced embedded systems. Its design is a testament to Roa Logic's commitment to delivering high-performance, adaptable IP solutions to the semiconductor industry.
The NMP-350 is a cutting-edge endpoint accelerator designed to optimize power usage and reduce costs. It is ideal for markets like automotive, AIoT/sensors, and smart appliances. Its applications span from driver authentication and predictive maintenance to health monitoring. With a capacity of up to 1 TOPS and 1 MB of local memory, it incorporates a RISC-V/Arm Cortex-M 32-bit CPU and supports three AXI4 interfaces. This makes the NMP-350 a versatile component for various industrial applications, ensuring efficient performance and integration. Developed as a low-power solution, the NMP-350 is pivotal for applications requiring efficient processing power without inflating energy consumption. It is crucial for mobile and battery-operated devices where every watt conserved adds to the operational longevity of the product. This product aligns with modern demands for eco-friendly and cost-effective technologies, supporting enhanced performance in compact electronic devices. Technical specifications further define its role in the industry, exemplifying how it brings robust and scalable solutions to its users. Its adaptability across different applications, coupled with its cost-efficiency, makes it an indispensable tool for developers working on next-gen AI solutions. The NMP-350 is instrumental for developers looking to seamlessly incorporate AI capabilities into their designs without compromising on economy or efficiency.
The NMP-550 is tailored for enhanced performance efficiency, serving sectors like automotive, mobile, AR/VR, drones, and robotics. It supports applications such as driver monitoring, image/video analytics, and security surveillance. With a capacity of up to 6 TOPS and 6 MB local memory, this accelerator leverages either a RISC-V or Arm Cortex-M/A 32-bit CPU. Its three AXI4 interface support ensures robust interconnections and data flow. This performance boost makes the NMP-550 exceptionally suited for devices requiring high-frequency AI computations. Typical use cases include industrial surveillance and smart robotics, where precise and fast data analysis is critical. The NMP-550 offers a blend of high computational power and energy efficiency, facilitating complex AI tasks like video super-resolution and fleet management. Its architecture supports modern digital ecosystems, paving the way for new digital experiences through reliable and efficient data processing capabilities. By addressing the needs of modern AI workloads, the NMP-550 stands as a significant upgrade for those needing robust processing power in compact form factors.
xcore.ai is a powerful platform tailored for the intelligent IoT market, offering unmatched flexibility and performance. It boasts a unique multi-threaded micro-architecture that provides low-latency and deterministic performance, perfect for smart applications. Each xcore.ai contains 16 logical cores distributed across two multi-threaded processor tiles, each equipped with 512kB of SRAM and capable of both integer and floating-point operations. The integrated interprocessor communication allows high-speed data exchange, ensuring ultimate scalability across multiple xcore.ai SoCs within a unified development environment.
The RISC-V Core-hub Generators from InCore are tailored for developers who need advanced control over their core architectures. This innovative tool enables users to configure core-hubs precisely at the instruction set and microarchitecture levels, allowing for optimized design and functionality. The platform supports diverse industry applications by facilitating the seamless creation of scalable and customizable RISC-V cores. With the RISC-V Core-hub Generators, InCore empowers users to craft their own processor solutions from the ground up. This flexibility is pivotal for businesses looking to capitalize on the burgeoning RISC-V ecosystem, providing a pathway to innovation with reduced risk and cost. Incorporating feedback from leading industry partners, these generators are designed to lower verification costs while accelerating time-to-market for new designs. Users benefit from InCore's robust support infrastructure and a commitment to simplifying complex chip design processes. This product is particularly beneficial for organizations aiming to integrate RISC-V technology efficiently into their existing systems, ensuring compatibility and enhancing functionality through intelligent automation and state-of-the-art tools.
The Y180 is a compact CPU-only design, serving as a clone of the Zilog Z180 CPU, and involves approximately 8K gates. It caters to applications that require compatibility with the Zilog architecture and prefer a minimalistic yet effective microprocessor implementation.
The RISC-V CPU IP N Class is designed to cater to the needs of 32-bit microcontroller units (MCUs) and AIoT (Artificial Intelligence of Things) applications. It is engineered to provide a balance of performance and power efficiency, making it suitable for a range of general computing needs. With its adaptable architecture, the N Class processor allows for customization, enabling developers to configure the core to meet specific application requirements while minimizing unnecessary overhead. Incorporating the RISC-V open standard, the N Class delivers robust functional features, supporting both security and functional safety needs. This processor core is ideal for applications that require reliable performance combined with low energy consumption. Developers benefit from an extensive set of resources and tools available in the RISC-V ecosystem to facilitate the integration and deployment of this processor across diverse use cases. The RISC-V CPU IP N Class demonstrates excellent scalability, allowing for configuration that aligns with the specific demands of IoT devices and embedded systems. Whether for implementing sophisticated sensor data processing or managing communication protocols within a smart device, the N Class provides the foundation necessary for developing innovative and efficient solutions.
Wormhole is a high-efficiency processor designed to handle intensive AI processing tasks. Featuring an advanced architecture, it significantly accelerates AI workload execution, making it a key component for developers looking to optimize their AI applications. Wormhole supports an expansive range of AI models and frameworks, enabling seamless adaptation and deployment across various platforms. The processor’s architecture is characterized by high core counts and integrated system interfaces that facilitate rapid data movement and processing. This ensures that Wormhole can handle both single and multi-user environments effectively, especially in scenarios that demand extensive computational resources. The seamless connectivity supports vast memory pooling and distributed processing, enhancing AI application performance and scalability. Wormhole’s full integration with Tenstorrent’s open-source ecosystem further amplifies its utility, providing developers with the tools to fully leverage the processor’s capabilities. This integration facilitates optimized ML workflows and supports continuous enhancement through community contributions, making Wormhole a forward-thinking solution for cutting-edge AI development.
The C100 is designed to enhance IoT connectivity and performance with its highly integrated architecture. Built around a robust 32-bit RISC-V CPU running up to 1.5GHz, this chip offers powerful processing capabilities ideal for IoT applications. Its architecture includes embedded RAM and ROM memory, facilitating efficient data handling and computations. A prime feature of the C100 is its integration of Wi-Fi components and various transmission interfaces, enhancing its utility in diverse IoT environments. The inclusion of an ADC, LDO, and a temperature sensor supports myriad applications, ensuring devices can operate in a wide range of conditions and applications. The chip's low power consumption is a critical factor in this design, enabling longer operation duration in connected devices and reducing maintenance frequency due to less charging or battery replacement needs. This makes the C100 chip suitable for secure smart home systems, interactive toys, and healthcare devices.
The SCR7 is a 64-bit RISC-V application core crafted to meet high-performance demands of applications requiring powerful data processing. Featuring a sophisticated dual-issue pipeline with out-of-order execution, it enhances computational efficiency across varied tasks. The core is equipped with a robust floating-point unit and supports extensive RISC-V ISA extensions for advanced computing capabilities. SCR7's memory system includes L1 to L3 caches, with options for expansive up to 16MB L3 caching, ensuring data availability and integrity in demanding environments. Its multicore architecture supports up to eight cores, facilitating intensive computational tasks across industries such as AI and machine learning. Ideal for high-performance computing and big data applications, the SCR7 leverages its advanced interrupt systems and intelligent memory management for seamless operation. Comprehensive development resources, from simulators to SDKs, augment its integration across Linux-based systems, accelerating project development timelines.
The Intelligence X280 is engineered to provide extensive capabilities for artificial intelligence and machine learning applications, emphasizing a software-first design approach. This high-performance processor supports vector and matrix computations, making it adept at handling the demanding workloads typical in AI-driven environments. With an extensive ALU and integrated VFPU capabilities, the X280 delivers superior data processing power. Capable of supporting complex AI tasks, the X280 processor leverages SiFive's advanced vector architecture to allow for high-speed data manipulation and precision. The core supports extensive vector lengths and offers compatibility with various machine learning frameworks, facilitating seamless deployment in both embedded and edge AI applications. The Intelligence family, represented by the X280, offers solutions that are not only scalable but are customizable to particular workload specifications. With high-bandwidth interfaces for connecting custom engines, this processor is built to evolve alongside AI's progressive requirements, ensuring relevance in rapidly changing technology landscapes.
NeuroMosAIc Studio is a comprehensive software platform designed to maximize AI processor utilization through intuitive model conversion, mapping, simulation, and profiling. This advanced software suite supports Edge AI models by optimizing them for specific application needs. It offers precision analysis, network compression, and quantization tools to streamline the process of deploying AI models across diverse hardware setups. The platform is notably adept at integrating multiple AI functions and facilitating edge training processes. With tools like the NMP Compiler and Simulator, it allows developers to optimize functions at different stages, from quantization to training. The Studio's versatility is crucial for developers seeking to enhance AI solutions through customized model adjustments and optimization, ensuring high performance across AI systems. NeuroMosAIc Studio is particularly valuable for its edge training support and comprehensive optimization capabilities, paving the way for efficient AI deployment in various sectors. It offers a robust toolkit for AI model developers aiming to extract the maximum performance from hardware in dynamic environments.
Micro Magic offers a state-of-the-art 64-bit RISC-V core known for its ultra-low power consumption, clocking in at just 10mW when operating at 1GHz. This processor harnesses advanced design techniques that allow it to achieve high performance while maintaining low operational voltages, optimizing energy efficiency. This processor stands out for its capability to deliver impressive processing speeds, reaching up to 5GHz under optimal conditions. It is designed with power conservation in mind, making it ideal for applications where energy efficiency is critical without sacrificing processing capability. The core is part of Micro Magic’s commitment to pushing the boundaries of low-power processing technology, making it suitable for a variety of high-speed computing tasks. Its design is particularly advantageous in environments demanding swift data processing and minimal power use, reaffirming Micro Magic’s reputation for pioneering efficient silicon solutions.
SiFive's Essential family of processor cores is designed to offer flexible and scalable performance for embedded applications and IoT devices. These cores provide a wide range of custom configurations that cater to specific power and area requirements across various markets. From minimal configuration microcontrollers to more complex, Linux-capable processors, the Essential family is geared to meet diverse needs while maintaining high efficiency. The Essential lineup includes 2-Series, 6-Series, and 7-Series cores, each offering different levels of scalability and performance efficiency. The 2-Series, for instance, focuses on power optimization, making it ideal for energy-constrained environments. The 6-Series and 7-Series expand these capabilities with richer feature sets, supporting more advanced applications with scalable infrastructure. Engineered for maximum configurability, SiFive Essential cores are equipped with robust debugging and tracing capabilities. They are customizable to optimize integration within System-on-Chip (SoC) applications, ensuring reliable and secure processing across a wide range of technologies. This ability to tailor the core designs ensures that developers can achieve a seamless balance between performance and energy consumption.
Tensix Neo represents the next evolution in AI processing, offering robust capabilities for handling modern AI challenges. Its design focuses on maximizing performance while maintaining efficiency, a crucial aspect in AI and machine learning environments. Tensix Neo facilitates advanced computation across multiple frameworks, supporting a range of AI applications. Featuring a strategic blend of core architecture and integrated memory, Tensix Neo excels in both processing speed and capacity, essential for handling comprehensive AI workloads. Its architecture supports multi-threaded operations, optimizing performance for parallel computing scenarios, which are common in AI tasks. Tensix Neo's seamless connection with Tenstorrent's open-source software environment ensures that developers can quickly adapt it to their specific needs. This interconnectivity not only boosts operational efficiency but also supports continuous improvements and feature expansions through community contributions, positioning Tensix Neo as a versatile solution in the landscape of AI technology.
The Spiking Neural Processor T1 is a microcontroller tailored for ultra-low-power applications demanding high-performance pattern recognition at the sensor edge. It features an advanced neuromorphic architecture that leverages spiking neural network engines combined with RISC-V core capabilities. This architecture allows for sub-milliwatt power dissipation and sub-millisecond latency, enabling the processor to conduct real-time analysis and identification of embedded patterns in sensor data while operating in always-on scenarios. Additionally, the T1 provides diverse interfaces, making it adaptable for use with various sensor types.
The SCR6 is a high-performance microcontroller core optimized for demanding embedded applications requiring substantial computational power. Its out-of-order 12-stage pipeline, complemented by a superscalar architecture, enhances processing speeds, making it ideal for real-time systems. Supporting a wide range of RISC-V ISA extensions, including cryptography and bit manipulation, SCR6 caters to secure and efficient data operations. The SCR6's memory subsystem is robust, featuring dual-level caches augmented with an L3 network-on-chip option. This rich memory architecture, along with efficient interrupt processing via APLIC units, ensures smooth high-speed data throughput in intensive applications. The core supports heterogeneous multicore configurations, enhancing parallel task execution. Designed for industrial and IoT environments, SCR6 comes with extensive development support. Its toolkit includes simulations, FPGA-based SDKs, and integration resources, facilitated through industry-standard interfaces, ensuring rapid development cycles and application deployment.
The Codasip RISC-V BK Core Series is designed to offer highly performant solutions suitable for a range of tasks from embedded applications to more demanding compute environments. By leveraging the RISC-V architecture, the BK Core Series provides a balance of power efficiency and processing capability, which is ideal for IoT edge applications and sensor controllers. The series is built around the philosophy of flexibility, allowing for modifications and enhancements to meet specific application requirements, including the integration of custom instructions to accommodate special workloads. This series also supports functional safety and security measures as outlined by industry standards, ensuring a robust foundation for critical applications.
AheadComputing offers an advanced RISC-V Core IP optimized for high-performance applications. These cores are crafted to enhance instruction per cycle (IPC) and power efficiency, making them ideal for cutting-edge processors demanding robust and reliable performance. By integrating the RISC-V Core into their designs, businesses can leverage a customizable and scalable architecture for their specific application needs. The RISC-V Core from AheadComputing demonstrates superior speed, a testament to their team’s deep expertise in processor technology. It allows seamless integration into existing infrastructure, offering flexibility and adaptability across various applications. The core is engineered to support a wide range of process nodes, ensuring compatibility and longevity in the dynamic tech industry. Standout features include the core's streamlined implementation process and its ability to significantly reduce time-to-market for new products. These cores represent not only a technological advancement but also a strategic resource that empowers companies to maintain a competitive edge in an ever-evolving marketplace.
The Y180S differentiates itself as a safe-state version of the Z180 CPU, accommodating around 10K gates. It is designed for environments where robust error-handling and reliability are crucial, offering enhanced stability and integrity for mission-critical applications.
The NeuroSense is a compact AI chip designed specifically for wearable devices, featuring neuromorphic analog signal processing technology. Its main focus lies in resolving common challenges faced by wearable tech, such as high power consumption, and limited battery life. By enabling highly accurate heart rate monitoring and activity recognition, this chip facilitates better fitness tracking without excessively draining battery resources. The NeuroSense's capability of operating independently from cloud connections addresses significant privacy concerns and data latency issues. It excels in delivering enhanced accuracy in heart rate measurements by utilizing a simple photoplethysmogram (PPG) configuration, which involves minimalistic hardware components like two LEDs and one photodiode. Through this setup, it achieves precision in bio-signal extraction far beyond conventional algorithmic methods, particularly when the wearer is in motion. Furthermore, the NeuroSense empowers wearables with advanced features like learning and recognizing user-specific activity patterns. With ultra-low power consumption and a compact size, the NeuroSense enables manufacturers to preserve space within constrained wearable designs while simultaneously enhancing battery life—solving a key concern in the realm of constantly operating smart devices.
ASIC North's Sensor Interface Derivatives are specialized circuits designed to enhance sensor systems by improving their performance and integration into broader network architectures. These derivatives offer reliable operation across a wide range of applications, ensuring robust performance even in challenging environments. With a focus on customizability, the designs are adaptable to meet specific client needs, facilitating the development of efficient sensor networks.
The AIoT Platform from SEMIFIVE is crafted to create specialized IoT and edge processing devices with efficiency and cutting-edge technology. Leveraging silicon-proven design components on Samsung's 14nm process, it streamlines the development of high-performance, power-efficient applications. This platform is equipped with dual SiFive U54 RISC-V CPUs, LPDDR4 memory, and comprehensive interfaces like MIPI-CSI and USB3.0. Targeted at consumer electronics such as wearables and smart home devices, this platform supports a wide array of IoT applications, including industrial IoT and smart security systems. Its architectural flexibility allows customization of system specifications, enabling designers to address the unique requirements of diverse IoT deployments. The AIoT platform supports applications with rigorous demands for power efficiency and cost-effectiveness, ensuring swift time-to-market and reduced development cycles. With a collaborative ecosystem of package design, board evaluation, and software, it paves the way for innovative IoT solutions that seamlessly integrate advanced technologies into everyday devices.
The Chimera Software Development Kit (SDK) by Quadric empowers developers with a robust platform to create and deploy complex AI and machine learning applications efficiently. It offers tools for developing, simulating, profiling, and deploying software, perfectly adaptable for Quadric’s Chimera GPNPU. The SDK simplifies coding by allowing integration of machine learning graph code with traditional C++ code into a singular, streamlined programming flow. This SDK includes the Chimera LLVM C++ compiler which utilizes state-of-the-art compiler infrastructure tailored to Chimera's specific instruction sets, driving efficiency and optimization. The SDK is compatible with Docker environments, enabling seamless on-premises or cloud-based deployment. This flexibility supports the versatile development needs of corporates working with private proprietary models while streamlining the toolchain for increased productivity. Its Graph Compiler transcodes machine learning inference models from popular frameworks like TensorFlow and PyTorch into optimized C++ using the Chimera Compute Library. This feature ensures that even the most complex AI models are efficiently deployed, lowering computational overheads and maximizing processing potential. Hence, the Chimera SDK serves as an invaluable tool for engineers aiming to expedite the deployment of cutting-edge ML algorithms both effectively and swiftly.
Grayskull is Tenstorrent's flagship product specifically designed to enhance AI and machine learning workloads. This high-performance solution provides optimized computing power through its use of advanced architectural design, tailored for efficient AI processing. Grayskull supports diverse applications, providing developers with the flexibility to implement and scale across various AI frameworks. Equipped with numerous cores and integrated memory capabilities, Grayskull offers a robust platform that caters to both training and inference operations. It excels in handling large datasets and complex model computations, delivering superior throughput and latency management which are crucial for AI tasks. The design is also power-efficient, making it an ideal choice for institutions aiming to maximize performance while managing power consumption. Grayskull is fully supported by Tenstorrent’s open-source software stack, which enhances its integration capabilities with pre-existing systems. By aligning with popular AI frameworks and encouraging community-driven improvements, Grayskull represents a strategic investment for industries looking to push the envelope in artificial intelligence.
The Akida1000 Reference SoC is a fully functional silicon solution designed to demonstrate the capabilities of BrainChip's neuromorphic AI technology. Built to showcase the potential of the Akida architecture, this SoC integrates the neural processor with a variety of connectivity options and memory interfaces, allowing for comprehensive evaluation in real-world settings.\n\nThis reference chip is ideal for developers and businesses looking to explore AI's vast applications at the edge, offering a seamless way to prototype and build AI systems without cloud dependency. The Akida1000 is engineered to function as either an embedded accelerator or a standalone AI coprocessor, supporting a breadth of use cases requiring efficient on-device data processing.\n\nAkida1000's flexibility and high performance make it suitable for diverse industries including automotive, healthcare, and industrial sectors, facilitating predictive analytics and complex problem-solving where traditional processors might struggle. Its design includes standard interfaces like PCIe, USB, and various I/O options, making it easily integrable into existing infrastructures.
The i.MX RT700 Crossover MCU is a part of NXP's dynamic series of microcontrollers, characterized by its high performance and integrated feature set, designed specifically for AI-enabled edge devices. It carries the distinction of having five computing cores, contributing to its robust handling of intensive processing tasks. Within automotive and IoT domains, the i.MX RT700 excels by providing unprecedented computing power and integration. This crossover microcontroller balances the needs of hardware functionality with seamless software integration, which is vital for deploying advanced smart systems. Ideal for situations that demand optimal interaction between various components, the RT700 facilitates AI processes, driving forward features like voice and speech recognition, which are increasingly being integrated into consumer electronics. Its features make it indispensable for innovative edge devices aiming to push technological boundaries.
The Y8002 microprocessor is engineered as a compact clone of a Zilog device, involving approximately 15K gates. It is tailored for use in systems that benefit from the functional mimicry of its Zilog counterpart, delivering consistent performance and compatibility for integrated designs.
Dedicated to energy-efficient computing, SkyeChip's Low Power RISC-V CPU IP offers a streamlined design utilizing the RV32 instruction set, with full support for base integer operations and extensions like M and C. This makes it a versatile processor core for embedded applications requiring minimal power. The CPU is tailored for machine mode operations with features such as vectored interrupts and standard debugging, in line with RISC-V specifications. This ensures great adaptability across various embedded systems looking for a balance between performance and power consumption. Ideal for IoT devices and applications demanding efficient processing with a small footprint, this IP supports a broad spectrum of applications while adhering to industry standards for low power consumption. It is a key component for developers focusing on optimizing performance without expending excessive energy.
Tailored for 64-bit architectures, the RISC-V CPU IP NX Class is crafted to cater to demanding applications requiring advanced processing capabilities. It's particularly well-suited for storage solutions and the burgeoning fields of augmented reality (AR), virtual reality (VR), and artificial intelligence (AI). With its robust architecture, the NX Class processor is capable of handling intensive computational tasks efficiently. The NX Class offers an expansive feature set that ensures high performance and functionality across a diverse range of applications. Utilizing the RISC-V standards, the NX Class provides implementers with the flexibility to customize their solutions, ensuring that the processor meets specific operational and performance criteria essential for high-end applications. Developers benefit from a rich software ecosystem for the NX Class, which includes comprehensive tools and libraries that support rapid development and innovation. The processor is well-equipped to facilitate the development of next-generation products that require powerful processing cores, ensuring that integrators can deliver cutting-edge solutions to markets that demand reliability, speed, and scalability.
The TSP1 Neural Network Accelerator is a state-of-the-art AI chip designed for versatile applications across various industries, including voice interfaces, biomedical monitoring, and industrial IoT. Engineered for efficiency, the TSP1 handles complex workloads with minimal power usage, making it ideal for battery-powered devices. This AI chip is capable of advanced bio-signal classification and natural voice interface integration, providing self-contained processing for numerous sensor signal applications. A notable feature is its high-efficiency neural network processing element fabric, which empowers signal pattern recognition and other neural network tasks, thereby reducing power, cost, and latency. The TSP1 supports powerful AI inference processes with low latency, enabling real-time applications like full vocabulary speech recognition and keyword spotting with minimal energy consumption. It's equipped with multiple interfaces for seamless integration and offers robust on-chip storage for secure network and firmware management. The chip is available in various packaging options to suit different application requirements.
TT-Ascalon™ is tailored for developers seeking high performance in AI computing. With its innovative design, it delivers exceptional computational efficiency, enabling the smooth execution of complex AI workloads. TT-Ascalon™ is part of Tenstorrent's strategic approach to offer scalable solutions that address the growing needs of AI and machine learning domains. The design of TT-Ascalon™ incorporates numerous processing cores and extensive memory capabilities, optimizing it for both training and inference tasks in machine learning applications. This IP is engineered to handle significant AI workloads, providing excellent performance metrics such as speed and throughput, crucial for high-stakes computational tasks. It also aligns with power efficiency standards, making it suitable for sustainable tech environments. A key feature of TT-Ascalon™ is its interoperability with Tenstorrent's open-source software ecosystem, which fosters adaptability and supports ongoing development across diverse platforms. By harnessing community-driven innovation, it stands out as a robust solution for organizations aiming to enhance AI processing capabilities while staying aligned with open technology principles.
The RISC-V Processor Core offers a highly flexible and customizable platform for a wide range of applications, from embedded devices to larger computing systems. Built on the open RISC-V architecture, it allows for innovations without proprietary restrictions. This core is engineered for optimal performance and power efficiency, making it an ideal choice for applications demanding both high-speed processing and energy conservation. Its scalability and modularity ensure adaptability to future technological advancements and diverse application requirements.
The Origami Programmer is a sophisticated configuration tool for Menta’s eFPGA architecture. This software stands out for delivering an easy-to-use interface, which simplifies the complex tasks of synthesis, place-and-route, and static timing analysis. Designed to optimize RTL specifically for the Menta eFPGA, Origami Programmer enables designers to bypass the need for additional FPGA configuration tools. Within its intuitive environment, users can benefit from a range of functionalities, such as an embedded Verific parser for synthesizing designs written in VHDL, Verilog, or SystemVerilog. The tool provides comprehensive analysis capabilities, including complete path and setup/hold reports, ensuring thorough insights into the design's performance metrics. Aimed at improving the design process efficiency, Origami Programmer supports various technology nodes and libraries, permitting performance estimations and resources optimization directly. This seamless integration and the ability to adapt configurations efficiently make Origami Programmer an indispensable asset in eFPGA design and implementation.
The ARM M-Class ASICs offered by ASIC North includes a wide range of ARM Cortex-M microcontrollers and processors. These chips can be integrated into a variety of existing systems across multiple industries. They are designed to offer flexibility and efficiency, providing solutions that meet the unique requirements of complex systems. The architectures are silicon-proven and include support for a variety of applications, from simple controller tasks to complex control systems.
The BA51 is a 32-bit RISC-V processor core designed for ultra-low-power applications. It features a dual-stage pipeline capable of operating at frequencies over 500 MHz when implemented in smaller process nodes like 16nm. This core is ideally suited for energy-efficient embedded systems, providing a balance of performance and silicon resource conservation. The compact design leverages advanced power-saving techniques, including clock gating and frequency scaling, to minimize energy consumption and maximize battery life. The BA51 is excellent for IoT and portable device applications where power efficiency is paramount, and it delivers robust computational capabilities without compromising on power usage.
Advanced Silicon's Specialty Microcontrollers set a new standard in high-performance computing with their integration of cutting-edge RISC-V architectures and advanced coprocessing capabilities. These MCUs are tailored for demanding applications requiring precise and rapid data processing, including image processing and complex algorithm execution. The specialty microcontrollers boast sophisticated features like embedded algorithms that cater to modern interactive touchscreen and machine learning applications. They perfectly complement Advanced Silicon's touch components, providing high levels of user interface innovation, system reliability, and operational efficiency. Whether for small-scale or expansive digital touch interfaces, these MCUs offer the processing power and integration needed to meet the demands of interactive technology solutions. Advanced Silicon continues to enhance these MCUs’ feature sets, keeping them at the forefront of technological capabilities in computing and interfacing systems.
The ARC Processor IP provided by Synopsys stands out with its customizable architecture tailored for a variety of embedded system applications. This processor IP supports 32-/64-bit execution, featuring an extensible instruction set that can be modified for specific processing needs. Suitable for automotive applications requiring real-time performance, the ARC Processor IP delivers energy-efficient operations, essential for applications like IoT devices and mobile computing. Additionally, the processor infrastructure is supported by a comprehensive toolchain, enabling developers to fine-tune software performance to boost system efficiency. Its low power and high-performance capabilities make it a preferred choice for modern, versatile embedded designs.
The Edge AI Neural Network Fabric 2.0 from Uniquify signifies a leap in AI-driven technology for next-generation neural networks. Designed to support advanced network models like CNN, RNN, and GANs, this fabric offers a comprehensive solution for machine learning applications requiring efficiency and scalability. Aimed at reducing the power and area footprint, Edge AI Neural Network Fabric 2.0 is engineered to be cost-effective while maintaining high-performance standards. Its application spans across IoT, smart devices, and any AI/ML driven systems, ensuring robust performance given diverse operational constraints. This cutting-edge technology provides an optimized platform for implementing AI solutions in silicon, making it a preferred choice for industries pursuing advancements in artificial intelligence and machine learning. With its innovative approach, it enables products to achieve superior performance without compromising on size, cost, or power efficiency.
The RFicient chip, designed for Internet of Things (IoT) applications, is renowned for its energy efficiency and wireless communication capabilities. This chip has been exactly engineered to drastically reduce power consumption, making it a pivotal component in sustainable IoT solutions. It plays a critical role in IoT devices, seeking to maximize data transmission while minimizing energy use, catering to an ever-expanding network of interconnected devices. By utilizing the RFicient chip, users can leverage advancements in technology while ensuring beneficial environmental impacts. One notable feature of the RFicient chip is its capability to handle a massive volume of messages daily, making it integral to Industrial IoT applications that require robust and reliable communication streams. Its adaptability allows deployment across various IoT domains, thus supporting varied applications, from smart agriculture to industrial automation. The innovation behind the RFicient chip lies in its capacity to perform effectively within sub-GHz spectrum ranges, ensuring long-range connectivity and resilience against interference. This makes it an attractive solution for environments that require a stable, far-reaching, and energy-frugal connectivity option. Its adoption is set to enhance efficiency and sustainability across industries that depend on IoT technologies.
The Y90 is a high-performance implementation of the Zilog Z180, structured with either 10K or 17K gates, depending on its configuration. It is developed for applications that require enhanced processing capabilities while maintaining the traditional Z180 architecture.
The Magnetic Hall Sensor developed at SystematIC Design is engineered to perform reliably across extended temperature ranges from -40°C to 110°C, offering an exceptional degree of sensitivity and precise current sensing capabilities. It operates with a 5.0 V single power supply, ensuring efficient energy consumption without compromising on performance. A standout feature of this sensor is its minimal magnetic hysteresis combined with low offset and thermal coefficients (TC), enhancing the accuracy of measurements. Designed to handle high dynamics, the sensor maintains operational stability even under substantial common-mode transients greater than 25kV/µs, which is crucial for industrial environments characterized by high electromagnetic interference. Moreover, the device provides a typical bandwidth of 80 kHz, making it an optimal choice for dynamic applications requiring swift response and reliable detection with minimal total output error, typically around ±1.5%. The robust design is further validated by certifications such as UL and CSA, ensuring high isolation voltage up to 3 kV RMS for one minute. With capabilities to accurately measure current ranges from ±10 A to ±30 A, this sensor proves indispensable for integration into applications demanding high precision and stability under rigorous conditions.
Application Specific Instruction-set Processors (ASIPs) from Wasiela provide highly specialized, programmable hardware accelerators designed to excel in specific application domains. By offering an instruction set tailored to particular tasks, ASIPs achieve optimal performance and efficiency in processing. These processors are pivotal in demanding fields where low power and high configurability are paramount. They stand as versatile solutions in Wasiela's portfolio, adaptable for a broad range of digital systems needing customized computing power.
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