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 2nd Generation Akida builds upon BrainChip's neuromorphic legacy, broadening the range of supported complex network models with enhancements in weight and activation precision up to 8 bits. This generation introduces additional energy efficiency, performance optimizations, and greater accuracy, catering to a broader set of intelligent applications. Notably, it supports advanced features like Temporal Event-Based Neural Networks (TENNs), Vision Transformers, and extensive use of skip connections, which elevate its capabilities within spatio-temporal and vision-based applications. Designed for a variety of industrial, automotive, healthcare, and smart city applications, the 2nd Generation Akida boasts on-chip learning which maintains data privacy by eliminating the need to send sensitive information to the cloud. This reduces latency and secures data, crucial for future autonomous and IoT applications. With its multipass processing capabilities, Akida addresses the challenge of limited hardware resources smartly, processing complex models efficiently on the edge. Offering a flexible and scalable IP platform, it is poised to enhance end-user experiences across various industries by enabling efficient real-time AI processing on compact devices. The introduction of long-range skip connections further supports intricate neural networks like ResNet and DenseNet, showcasing Akida's potential to drive deeper model efficiencies without excessive host CPU calculation dependence.
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 Origin E1 is an optimized neural processing unit (NPU) targeting always-on applications in devices like home appliances, smartphones, and security cameras. It provides a compact, energy-efficient solution with performance tailored to 1 TOPS, making it ideal for systems needing low-power and minimal area. The architecture is built on Expedera's unique packet-based approach, which enables enhanced resource utilization and deterministic performance, significantly boosting efficiency while avoiding the pitfalls of traditional layer-based architectures. The architecture is fine-tuned to support standard and custom neural networks without requiring external memory, preserving privacy and ensuring fast processing. Its ability to process data in parallel across multiple layers results in predictive performance with low power and latency. Always-sensing cameras leveraging the Origin E1 can continuously analyze visual data, facilitating smoother and more intuitive user interactions. Successful field deployment in over 10 million devices highlights the Origin E1's reliability and effectiveness. Its flexible design allows for adjustments to meet the specific PPA requirements of diverse applications. Offered as Soft IP (RTL) or GDS, this engine is a blend of efficiency and capability, capitalizing on the full scope of Expedera's software tools and custom support features.
The ADAS and Autonomous Driving solutions from KPIT focus on advancing autonomy in vehicles by addressing key challenges in technology, regulatory compliance, and consumer trust. The solutions include rigorous testing environments and simulation frameworks to explore corner cases and ensure safety. KPIT's autonomous driving solutions aim to enhance feature development, integrate AI-driven decision-making, and provide robust validation environments that empower automakers to deliver safer, reliable autonomous vehicles.
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.
Altek's AI Camera Module stands as a testament to the company's prowess in integrating artificial intelligence with advanced imaging technology. This module is designed for a spectrum of applications that demand rapid and precise image processing, such as surveillance, automated inspection, and smart devices. By leveraging sophisticated AI algorithms, the module can perform real-time image analysis, enabling enhanced decision-making processes in demanding scenarios. The AI Camera Module is engineered to deliver high-resolution imagery, coupled with robust data processing capabilities that ensure seamless performance in dynamic environments. Its architecture supports a variety of AI-driven functions like facial recognition, object tracking, and behavioral pattern analysis, thereby elevating the module’s versatility across different sectors. Compatibility with IoT systems enhances its appeal, as the module facilitates sophisticated integration with broader networked environments. With a focus on reducing latency and boosting computational efficiency, Altek's AI Camera Module is poised to be a vital component in the future of smart cities and connected solutions.
The RV12 RISC-V Processor from Roa Logic is a highly adaptable, single-issue processor designed to comply with modern RISC-V standards, specifically targeting the embedded systems market. Structured around a 32-bit and 64-bit RISC-V instruction set, the processor employs a Harvard architecture to optimize the bandwidth of instruction and data accesses. It offers enhanced customization and configurability, allowing developers to adapt the processor for a variety of applications. This processor supports modular design approaches and can be efficiently integrated into both FPGA and ASIC designs, making it a versatile choice in the development of cutting-edge technologies. Its industry-standard compliance ensures ease of integration into existing systems that utilize RISC-V specifications, resulting in reduced development time and effort. As part of the broader RISC-V ecosystem promoted by Roa Logic, the RV12 boasts a robust architecture that facilitates experimental and commercial use, providing a solid foundation for innovation. Available for non-commercial purposes through a flexible licensing agreement, it supports the open movement towards collaborative digital innovation.
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 Origin E8 NPU by Expedera is engineered for the most demanding AI deployments such as automotive systems and data centers. Capable of delivering up to 128 TOPS per core and scalable to PetaOps with multiple cores, the E8 stands out for its high performance and efficient processing. Expedera's packet-based architecture allows for parallel execution across varying layers, optimizing resource utilization, and minimizing latency, even under strenuous conditions. The E8 handles complex AI models, including large language models (LLMs) and standard machine learning frameworks, without requiring significant hardware-specific changes. Its support extends to 8K resolutions and beyond, ensuring coverage for advanced visualization and high-resolution tasks. With its low deterministic latency and minimized DRAM bandwidth needs, the Origin E8 is especially suitable for high-performance, real-time applications. The high-speed processing and flexible deployment benefits make the Origin E8 a compelling choice for companies seeking robust and scalable AI infrastructure. Through customized architecture, it efficiently addresses the power, performance, and area considerations vital for next-generation AI technologies.
The RISC-V Core-hub Generators are sophisticated tools designed to empower developers with complete control over their processor configurations. These generators allow users to customize their core-hubs at both the Instruction Set Architecture (ISA) and microarchitecture levels, offering unparalleled flexibility and adaptability in design. Such capabilities enable fine-tuning of processor specifications to meet specific application needs, fostering innovation within the RISC-V ecosystem. By leveraging the Core-hub Generators, developers can streamline their chip design process, ensuring efficient and seamless integration of custom features. This toolset not only simplifies the design process but also reduces time-to-silicon, making it ideal for industries seeking rapid advancements in their technological capabilities. The user-friendly interface and robust support of these generators make them a preferred choice for developing cutting-edge processors. InCore Semiconductors’ RISC-V Core-hub Generators represent a significant leap forward in processor design technology, emphasizing ease of use, cost-effectiveness, and scalability. As demand for tailored and efficient processors grows, these generators are set to play a pivotal role in shaping the future of semiconductor design, driving innovation across multiple sectors.
The TimbreAI T3 is a premier AI inference engine from Expedera, designed specifically for audio noise reduction in power-sensitive devices like wireless headsets. Achieving up to 3.2 GOPS at an ultra-low power consumption of less than 300 µW, the T3 caters to devices with stringent power and area constraints. This product features Expedera's advanced packet-based architectural strategy, setting a new standard for efficiency in embedded AI applications. Ported easily across different foundries, the TimbreAI T3 ensures seamless performance without requiring alterations to pre-trained models, safeguarding accuracy and maintaining consistent results. Its comprehensive support for common audio neural networks and standard NN functions underscores its versatility and adaptability within varied use cases. Exemplified by successful integration in over 10 million devices globally, the T3 is proof of Expedera's commitment to delivering high-quality, energy-efficient semiconductor solutions. Coupled with expedited development and integration capabilities, this IP represents a vital component in enhancing audio processing capabilities across contemporary electronic devices.
xcore.ai is a versatile platform specifically crafted for the intelligent IoT market. It hosts a unique architecture with multi-threading and multi-core capabilities, ensuring low latency and high deterministic performance in embedded AI applications. Each xcore.ai chip contains 16 logical cores organized in two multi-threaded processor 'tiles' equipped with 512kB of SRAM and a vector unit for enhanced computation, enabling both integer and floating-point operations. The design accommodates extensive communication infrastructure within and across xcore.ai systems, providing scalability for complex deployments. Integrated with embedded PHYs for MIPI, USB, and LPDDR, xcore.ai is capable of handling a diverse range of application-specific interfaces. Leveraging its flexibility in software-defined I/O, xcore.ai offers robust support for AI, DSP, and control processing tasks, making it an ideal choice for enhancing IoT device functionalities. With its support for FreeRTOS, C/C++ development environment, and capability for deterministic processing, xcore.ai guarantees precision in performance. This allows developers to partition xcore.ai threads optimally for handling I/O, control, DSP, and AI/ML tasks, aligning perfectly with the specific demands of various applications. Additionally, the platform's power optimization through scalable tile clock frequency adjustment ensures cost-effective and energy-efficient IoT solutions.
The NMP-550 is tailored for enhanced performance efficiency, serving sectors like automotive, mobile, AR/VR, drones, and robotics. It supports applications such as driver monitoring, image/video analytics, and security surveillance. With a capacity of up to 6 TOPS and 6 MB local memory, this accelerator leverages either a RISC-V or Arm Cortex-M/A 32-bit CPU. Its three AXI4 interface support ensures robust interconnections and data flow. This performance boost makes the NMP-550 exceptionally suited for devices requiring high-frequency AI computations. Typical use cases include industrial surveillance and smart robotics, where precise and fast data analysis is critical. The NMP-550 offers a blend of high computational power and energy efficiency, facilitating complex AI tasks like video super-resolution and fleet management. Its architecture supports modern digital ecosystems, paving the way for new digital experiences through reliable and efficient data processing capabilities. By addressing the needs of modern AI workloads, the NMP-550 stands as a significant upgrade for those needing robust processing power in compact form factors.
The NaviSoC is a cutting-edge system-on-chip (SoC) that integrates a GNSS receiver and an application processor on one silicon die. Known for its high precision and reliability, it provides users with a compact and energy-efficient solution for various applications. Capable of supporting all GNSS bands and constellations, it offers fast time-to-first-fix, centimeter-level accuracy, and maintains high sensitivity even in challenging environments. The NaviSoC's flexible design allows it to be customized to meet specific user requirements, making it suitable for a wide range of applications, from location-based services to asset tracking and smart agriculture. The incorporation of a RISC-V application microcontroller, along with an array of peripherals and interfaces, introduces expanded functionality, optimizing it for advanced IoT and industrial applications. Engineered for power efficiency, the NaviSoC supports a range of supply voltages, ensuring low power consumption across its operations. The chip's design provides for efficient integration into existing systems with the support of a comprehensive SDK and IDE, allowing developers to tailor solutions to their precise needs in embedded systems and navigation infrastructures.
The Origin E2 from Expedera is engineered to perform AI inference with a balanced approach, excelling under power and area constraints. This IP is strategically designed for devices ranging from smartphones to edge nodes, providing up to 20 TOPS performance. It features a packet-based architecture that enables parallel execution across layers, improving resource utilization and performance consistency. The engine supports a wide variety of neural networks, including transformers and custom networks, ensuring compatibility with the latest AI advancements. Origin E2 caters to high-resolution video and audio processing up to 4K, and is renowned for its low latency and enhanced performance. Its efficient structure keeps power consumption down, helping devices run demanding AI tasks more effectively than with conventional NPUs. This architecture ensures a sustainable reduction in the dark silicon effect while maintaining high operating efficiencies and accuracy thanks to its TVM-based software support. Deployed successfully in numerous smart devices, the Origin E2 guarantees power efficiency sustained at 18 TOPS/W. Its ability to deliver exceptional quality across diverse applications makes it a preferred choice for manufacturers seeking robust, energy-conscious solutions.
The SCR7 Application Core is an epitome of advanced data processing capability within the RISC-V framework, designed to handle the computational requirements of sophisticated applications. This Linux-capable 64-bit core incorporates a dual-issue, out-of-order 12-stage pipeline featuring vector and cryptography extensions, optimizing operations for heavy data-centric workloads.\n\nIts memory subsystem includes robust L1, L2, and MMU configurations that equip the SCR7 with the prerequisite tools for expansive architectural frameworks. Support for dual-core multiprocessor configurations and efficient cache coherency ensures streamlined operations, catering to diverse processing needs across networked and AI applications.\n\nApplications in high-performance computing, AI, and networking thrive with the SCR7 core's energy-efficient, data-allied design. From video processing to computer vision, this core empowers developers to transcend traditional limitations, ushering in a new era of computational capability for enterprise and consumer technologies alike.
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.
Expedera's Origin E6 NPU is crafted to enhance AI processing capabilities in cutting-edge devices such as smartphones, AR/VR headsets, and automotive systems. It offers scalable performance from 16 to 32 TOPS, adaptable to various power and performance needs. The E6 leverages Expedera's packet-based architecture, known for its highly efficient execution of AI tasks, enabling parallel processing across multiple workloads. This results in better resource management and higher performance predictability. Focusing on both traditional and new AI networks, Origin E6 supports large language models as well as complex data processing tasks without requiring additional hardware optimizations. Its comprehensive software stack, based on TVM, simplifies the integration of trained models into practical applications, providing seamless support for mainstream frameworks and quantization options. Origin E6's deployment reflects meticulous engineering, optimizing memory usage and processing latency for optimal functionality. It is designed to tackle challenging AI applications in a variety of demanding environments, ensuring consistent high-performance outputs and maintaining superior energy efficiency for next-generation technologies.
The Y180 is a streamlined microprocessor design, incorporating approximately 8K gates and serving primarily as a CPU clone of the Zilog Z180. It caters to applications requiring efficient, compact processing power without extensive resource demands. Its design is particularly apt for systems that benefit from Z80 architecture compatibility, ensuring effortless integration and functionality within a variety of technological landscapes.
The Tyr Superchip is engineered to tackle the most daunting computational challenges in edge AI, autonomous driving, and decentralized AIoT applications. It merges AI and DSP functionalities into a single, unified processing unit capable of real-time data management and processing. This all-encompassing chip solution handles vast amounts of sensor data necessary for complete autonomous driving and supports rapid AI computing at the edge. One of the key challenges it addresses is providing massive compute power combined with low-latency outputs, achieving what traditional architectures cannot in terms of energy efficiency and speed. Tyr chips are surrounded by robust safety protocols, being ISO26262 and ASIL-D ready, making them ideally suited for the critical standards required in automotive systems. Designed with high programmability, the Tyr Superchip accommodates the fast-evolving needs of AI algorithms and supports modern software-defined vehicles. Its low power consumption, under 50W for higher-end tasks, paired with a small silicon footprint, ensures it meets eco-friendly demands while staying cost-effective. VSORA’s Superchip is a testament to their innovative prowess, promising unmatched efficiency in processing real-time data streams. By providing both power and processing agility, it effectively supports the future of mobility and AI-driven automation, reinforcing VSORA’s position as a forward-thinking leader in semiconductor technology.
The SCR6 Microcontroller Core is infused with high-performance attributes, optimizing operations for embedded RTOS applications requiring significant computational vigor. This silicon-proven, 64-bit RISC-V processor utilizes a 12-stage superscalar pipeline with out-of-order processing, enabling efficient execution of complex tasks. Complementing its high-precision floating-point unit are innovative cryptographic and bit manipulation extensions, broadening its functional scope across various domains.\n\nThis core supports multicore configurations accommodating up to 8 processors, alongside caches and a PMP unit that validate RTOS functionality. Standard interfaces like AXI4 and JTAG enrich its adaptability for embedded integrations, ensuring compatibility with evolving technology landscapes.\n\nDevelopers in industrial automation, motor control, image processing, and automotive systems benefit from the SCR6’s substantial computational capabilities. Its holistic design caters to advanced smart home and sensor fusion systems, delivering robust power and performance in an efficient, scalable format.
Akida IP is BrainChip's pioneering neuromorphic processor, crafted to mimic the human brain's analytic capabilities by processing only essential sensor inputs. This localized processing greatly enhances efficiency and privacy, as it significantly reduces the need for cloud data transactions. The processor offers scalable architecture supporting up to 256 nodes interconnected via a mesh network with each node composed of four configurable Neural Network Layer Engines. This event-based technology cuts down operations drastically compared to traditional methods, promoting lower power consumption. With robust support for on-chip learning and incremental learning capabilities, Akida IP is apt for a diverse range of applications and environments. The neural network processor adapts to real-time data seamlessly, creating new avenues for personalized and private on-device AI experiences. The architecture of Akida IP allows it to run complete neural networks, managing various neural network functions in hardware, thus optimizing resource utilization and power efficiency. Integrating Akida IP into systems is straightforward with BrainChip's development ecosystem, facilitating easy evaluation, design, and deployment processes. The Akida PCIe board and additional platform offerings, like the Raspberry Pi kit, promote seamless development and integration for intelligent AI endpoints, perfectly aligning with BrainChip's mission to streamline the implementation of edge AI solutions.
The SiFive Essential family of processors caters to a wide range of applications with its highly customizable IP cores. Designed to meet specific market needs, these processors range from small, power-efficient designs for microcontrollers to fully-featured, Linux-capable superscalar processors. Featuring configurable microarchitectures, the Essential family provides scalability in performance and power, making it an ideal choice for diverse applications from IoT to real-time control. The Essential series is highly adaptable, with series like the 2-Series offering power and area optimization through a 2-4 stage pipeline for embedded solutions. In contrast, the 6-Series and 7-Series provide extensive configurability with their 8-stage pipelines suited for more demanding applications requiring 32/64-bit capable systems. Emphasizing flexibility, the Essential family enables a mix-and-match capability, allowing designers to combine deterministic real-time processors with higher performance application cores. With built-in Trace + Debug capabilities and open-soc security features, the Essential processors provide an integrated solution for efficient and secure processing.
The Chipchain C100 is a sophisticated, single-chip solution designed for Internet of Things (IoT) applications. It is built around a 32-bit RISC-V CPU operating at speeds of up to 1.5GHz, supplemented by embedded RAM and ROM, ensuring exceptional computational efficiency. The C100 integrates several essential features for IoT use, including Wi-Fi capability, multiple data transmission interfaces, and built-in ADCs, LDOs, and temperature sensors. This integration is aimed at simplifying and expediting application development across various domains ranging from security to healthcare.
The RISC-V Core IP from AheadComputing represents a pinnacle of modern processor architecture. Specializing in 64-bit application processors, this IP is designed to leverage the open-standard RISC-V architecture, ensuring flexibility while pushing the boundaries of performance. Its architecture is tailored to deliver outstanding per-core performance, making it ideal for applications requiring significant computational power combined with the benefits of open-source standards. Engineered with efficiency and compatibility in mind, the RISC-V Core IP by AheadComputing caters to a wide array of applications, from consumer electronics to advanced computing systems. It supports the development of highly efficient CPUs that not only excel in speed but also offer scalability across different computing environments. This makes it a highly versatile choice for developers aiming to adopt a powerful yet adaptable processing core. The AheadComputing RISC-V Core IP is also known for its configurability, making it suitable for various market needs and future technological developments. Built on the experience and expertise of its development team, this IP remains at the frontier of innovative processor design, enabling clients to harness cutting-edge computing solutions prepped for next-generation challenges.
The Codasip RISC-V BK Core Series represents a lineup of processor cores that leverage the open standard architecture of RISC-V to deliver highly customizable computational solutions. These cores provide a balance between power efficiency and performance, making them ideal for a broad range of applications, including IoT devices and embedded systems. The BK series cores are designed to be versatile, supporting a variety of operating systems while allowing full customization to meet specific workload demands. This flexibility empowers designers to implement custom instructions and optimize the cores for particular applications without compromising on power budgets. The series is compliant with RISC-V standards, ensuring seamless integration with other RISC-V based solutions.
The Spiking Neural Processor T1 is an innovative ultra-low power microcontroller designed for always-on sensing applications, bringing intelligence directly to the sensor edge. This processor utilizes the processing power of spiking neural networks, combined with a nimble RISC-V processor core, to form a singular chip solution. Its design supports next-generation AI and signal processing capabilities, all while operating within a very narrow power envelope, crucial for battery-powered and latency-sensitive devices. This microcontroller's architecture supports advanced on-chip signal processing capabilities that include both Spiking Neural Networks (SNNs) and Deep Neural Networks (DNNs). These processing capabilities enable rapid pattern recognition and data processing similar to how the human brain functions. Notably, it operates efficiently under sub-milliwatt power consumption and offers fast response times, making it an ideal choice for devices such as wearables and other portable electronics that require continuous operation without significant energy draw. The T1 is also equipped with diverse interface options, such as QSPI, I2C, UART, JTAG, GPIO, and a front-end ADC, contained within a compact 2.16mm x 3mm, 35-pin WLCSP package. The device boosts applications by enabling them to execute with incredible efficiency and minimal power, allowing for direct connection and interaction with multiple sensor types, including audio and image sensors, radar, and inertial units for comprehensive data analysis and interaction.
Tailored specifically for AI and machine learning requirements at the edge, the SiFive Intelligence X280 brings powerful capabilities to data-intensive applications. This processor line is part of the high-performance AI data flow processors from SiFive, designed to offer scalable vector computation capabilities. Key features include handling demanding AI workloads, efficient data flow management, and enhanced object detection and speech recognition processing. The X280 is equipped with vector processing capabilities that include a 512-bit vector length, single vector ALU VCIX (1024-bit), plus a host of new instructions optimized for machine learning operations. These features provide a robust platform for addressing energy-efficient inference tasks, driven by the need for high-performance yet low-power computing solutions. Key to the X280's appeal is its ability to interface seamlessly with popular machine learning frameworks, enabling developers to deploy models with ease and flexibility. Additionally, its compatibility with SiFive Intelligence Extensions and TensorFlow Lite enhances its utility in delivering consistent, high-quality AI processing in various applications, from automotive to consumer devices.
An evolution of the Y180, the Y180S offers a safe-state version of its predecessor, encompassing approximately 10K gates. This enhanced version is tailored for applications where safety and state retention are critical, maintaining all the beneficial features of the Y180 while incorporating additional safety mechanisms. Its architecture remains compatible with Z80 instruction sets, ensuring consistent integration across platforms necessitating reliable and secure processing.
The Y8002 microprocessor is a replication of a known Zilog device, with a gate count of approximately 15K. Designed to offer consistent performance aligned with Zilog's benchmarks, it supports projects requiring both reliability and compatibility with Zilog's infrastructure. Its gate efficiency and operational familiarity make it an optimal choice for tasks needing precision alongside established interface standards.
The Yuzhen 600 RFID Chip embodies T-Head's expertise in developing ultra-efficient integrated circuits tailored for RFID applications, where low-power and high-performance standards are paramount. This chip is engineered to streamline RFID processes, ensuring swift and accurate reading and writing of tags even in dense environments. By adopting compact design principles, the Yuzhen 600 minimizes energy consumption while maximizing throughput speeds, ensuring extended operational life for applications in supply chain management and logistics. Equipped with sophisticated RF processing capabilities, the chip supports various RFID standards, making it versatile for global applications. Its robust design guarantees resilient performance under diverse environmental conditions, thereby enhancing reliability in critical operations. This adaptability extends to encryption features, ensuring data security and integrity during transactions and data exchanges. T-Head's Yuzhen 600 is optimized for integration into a wide range of applications, from retail inventory management to industrial asset tracking, offering businesses a dependable tool to enhance operational efficiency and reduce costs. Its presence in T-Head's diverse product portfolio highlights a commitment to advancing connected technologies.
The DQ80251 is a revolutionary microcontroller core, executing instructions with an ultra-high-performance quad-pipelined architecture. This core is optimized for both 16-bit and 32-bit embedded applications, offering unmatched speed and reliability. It supports classic 8051 instruction compatibility while pushing the limits with enhancements that accelerate processing power significantly. With a small gate size of 13,500 and the ability to handle 8MB code space, the DQ80251 core also climbs to a performance level of 75.08 DMIPS, making it a vital component in applications demanding quick data processing.
Sensor Interface Derivatives are critical in bridging the analog and digital realms, especially in the burgeoning Internet of Things (IoT) market. These devices convert various analog signals—like temperature, voltage, and geographical position—into digital form for seamless integration with digital systems. Designed for durability in varying environmental conditions, these interfaces ensure autonomous and long-lived battery performance. ASIC North's sensor interface solutions excel in managing radio communication interfaces and include built-in digital signal processing to filter data before transmission, enhancing efficiency. They feature a sensor concentrator capability that stimulates sensors while measuring responses across multiple channels, adeptly handling various signal types through robust interface circuits. With extensive experience in Analog to Digital and Digital to Analog conversion, ASIC North has successfully deployed millions of these interfaces with a high production yield, underscoring their reliability and quality. These interfaces not only withstand environmental stresses but also offer a long battery life, making them ideal for IoT applications.
The Low Power RISC-V CPU IP from SkyeChip delivers power-efficient processing tailored for embedded applications. It fully supports the RISC-V RV32 instruction set with complete support for the 'I' and 'C' subsets while offering machine mode operations and a vectorized interrupt framework. This optimizes the processor for low-power operation in constrained environments, making it ideal for innovative and flexible IoT applications.
The Wormhole processor from Tenstorrent is engineered for advanced AI applications, providing unmatched performance and scalability. It is an integral part of their Galaxy system, featuring 32 chips interconnected with an Ethernet-based mesh topology. This design facilitates rapid data exchange and processing, ideal for high-density computing environments. Equipped with Tensix cores, the Wormhole processor attains up to 9.3 PetaFLOPS, making it excellent for AI model training and inference tasks. The processor supports various floating-point formats, including FP8, FP16, and FP32, to deliver flexibility and precision in calculations. It also features a remarkable SRAM capacity, ensuring swift data access and processing efficiency. The Wormhole is not just about sheer processing power; it also integrates a sophisticated network-on-chip architecture to improve communication between cores. This allows developers to maximize throughput while maintaining power efficiency, essential for large-scale AI deployments. Additionally, system interfaces like high-speed Ethernet enhance its connectivity, making it suitable for integration into existing infrastructures. This processor's design exhibits flexibility by supporting features such as dynamic partitioning of compute resources. Its scalability and efficiency make it a robust choice for building next-gen AI infrastructures, catering to both edge and cloud deployments. With the Wormhole processor, Tenstorrent empowers organizations to tackle complex AI workflows with confidence and ease.
Advanced Silicon's Specialty Microcontrollers are architecturally innovative RISC-V based solutions tailored for high-performance applications like image processing. Encompassing cutting-edge co-processing units, these microcontrollers redefine potential in embedded system functionalities. The controllers integrate both performance and practicality, enabling sophisticated algorithms crucial for modern image processing tasks. They come embedded with touch firmware featuring machine learning algorithms that handle user input recognition, enhancing interactive user interfaces. This positions Advanced Silicon at the forefront of the industry, propelling user-friendly and intuitive technology solutions. Their SOC Touch Controllers are structured on a 32-bit RISC architecture, featuring integrated capacitive AFE interfaces, power management units, and robust communication interfaces, suited for smaller touch screens ranging between 10 to 27 inches. For larger screens, up to 84 inches, their multi-chip solutions combine advanced 32-bit DSP architecture with powerful capacitive sensing AFEs, offering comprehensive performance for interactive applications.
The TSP1 Neural Network Accelerator from Applied Brain Research is a cutting-edge AI solution built to handle complex AI workloads with remarkable efficiency. Designed specifically for battery-powered devices, this chip excels in low-power operations while processing extensive neural network tasks. At its core, the TSP1 integrates state-of-the-art processing capabilities tailored for time series data, essential for applications like natural voice interfaces and bio-signal classification. This innovative chip is notable for its energy efficiency, consuming less than 10mW for complex AI tasks, making it an ideal solution for energy-conscious applications. Furthermore, it supports an array of sensor signal applications, ensuring versatile functionality across different domains including AR/VR, smart home automation, and medical wearables. By incorporating the Legendre Memory Unit, a proprietary advanced state-space neural network model, the TSP1 achieves superior data efficiency compared to traditional network architectures. ABR’s TSP1 stands out for its ability to perform powerful AI inferences with low latency, essential for real-time applications. It supports a wide range of interfaces, making it suitable for diverse integration scenarios, from voice recognition to industrial automation. Additionally, the chip's optimized hardware is key for algorithm scaling, facilitating smooth processing of larger neural models without compromising speed or performance.
The RISC-V CPU IP N Class presents a powerful 32-bit architecture designed for microcontrollers and AIoT applications. Highly configurable to meet diverse application demands, this class supports robust security and functional safety features, making it suitable for a wide range of uses. The N Class confidently aligns with the stringent requirements of modern electronics while providing high-efficiency performance. This processor class benefits from an architecture that supports rapid customization, ensuring that each design can be finely tuned to optimize for specific functionalities and applications. Its compliance with the RISC-V standard assures users of open-source flexibility and interoperability with existing RISC-V ecosystems. Furthermore, the N Class comes with a wide array of development tools, including SDKs and RTOS support, facilitating seamless deployment. Emphasizing security, the N Class processors include features such as secure boot and encryption support. These processors are ideal for industries needing reliable and scalable computing, achieving high performance with low power consumption, making them a valuable asset for next-generation technological solutions.
The ARM M-Class Based ASICs provide a versatile platform leveraging the ARM® Cortex-M series of processors. These processors are ideal for building custom ASIC solutions that cater to varying processing needs across industries. By integrating different memory configurations and supporting multiple peripheral protocols, these ASICs can efficiently combine processing cores, sensors, and communication IP into a single cohesive solution. ASIC North capitalizes on this platform to develop an ASIC development platform aimed at custom ARM Cortex-M based devices, focusing on easy integration of complex circuit blocks. This solution addresses common challenges in development, such as achieving ultra-low power consumption and advanced security features, crucial for devices like IoT endpoints. With expertise in low power architecture, ASIC North designs devices capable of long, battery-based field deployments while ensuring robust data security through features like physically unclonable functions and hardware encryption. This comprehensive solution leverages the capabilities of the ARM platform and enriches device functionality with optimized software and firmware stacks.
Tensix Neo by Tenstorrent stands as a sophisticated processor designed to cater to intricate AI computations. Known for its superior handling of large-scale machine learning tasks, Tensix Neo prioritizes both performance and efficiency. The Tensix Neo processor provides a flexible platform for developers needing high computational power for AI algorithms. It handles multiple data types and supports a variety of machine learning models, delivering high precision and speed for inference and training sessions. Its architecture is optimized for parallel computing, facilitating concurrent data processing that accelerates workflow activities. Alongside exceptional memory bandwidth, the Tensix Neo ensures that data-intensive tasks do not overwhelm system resources, maintaining a balanced load across operations. This processor is ideal for various applications in deep learning and AI analysis, offering capabilities that go beyond the basics to push boundaries in AI research. Its adaptability makes it suitable for integration in different computing environments, from data centers to cloud-based platforms, demonstrating Tenstorrent's commitment to versatile, next-gen tech solutions.
Aiming to meet the growing demand for customizable and efficient processing solutions, the RISC-V Processor Core developed by Fraunhofer IPMS offers flexibility and scalability. This open-source architecture promotes innovation by allowing designers to optimize and extend core functionalities according to specific application needs. With its extensible instruction set architecture (ISA), this processor core is prime for applications that range from low-power devices to high-performance computing systems. The RISC-V Processor Core aligns with industry trends favoring open architectures, facilitating broad adoption across various sectors, including automotive, IoT, and aerospace. Notably, this processor underscores Fraunhofer IPMS’s commitment to continuous improvement and advanced research, driving the future of custom processing solutions by enabling efficient, adaptable, and high-performance applications well-suited for the dynamic tech landscape.
Designed to meet the growing demand for speed and efficiency in embedded systems, the i.MX RT700 Crossover Microcontroller Unit (MCU) combines high-performance processing with real-time operation capabilities. The RT700 MCU, currently in preproduction, is powered by five computing cores, ensuring unmatched performance in AI-driven and IoT applications. The i.MX RT700 excels with its ability to facilitate complex computations and seamless real-time data processing—a necessity for modern devices requiring quick response and accuracy. This makes it particularly beneficial for edge processing in smart tech solutions, offering a reliable backbone for AI systems and IoT infrastructures. Its comprehensive structure supports advanced multimedia applications, paving the way for innovations across various sectors by enhancing user interactions and overall device capabilities. This aligns it as a prime facilitator of cutting-edge technological growth, offering possibilities for developers to create more intuitive and powerful solutions.
Designed for 64-bit architecture, the RISC-V CPU IP NX Class addresses the demanding needs of storage, AR/VR, and AI applications. It is built to deliver exceptional performance across various high-intensity operations while maintaining a flexible and adaptable architecture. Ideal for advanced systems requiring high data throughput and sophisticated processing capabilities, the NX Class is equipped to power innovative technological solutions. With a strong emphasis on high-performance capabilities, the NX Class processors provide substantial computing power tailored for storage solutions and immersive computing applications like AR/VR. This makes them a top choice for industries pushing the boundaries of visual and data-driven experiences. The NX Class's incorporation of advanced security measures ensures that data integrity and secure operations are never compromised, making these processors a reliable backbone for mission-critical tasks. Supported by a comprehensive suite of development tools, including simulation environments and SDKs, the NX Class facilitates smooth integration and accelerated development cycles, fostering rapid innovation.
The Origami Programmer is a sophisticated eFPGA configuration tool, simplifying the design of custom architectures with an intuitive GUI. It automates the synthesis, placement, routing, and generates the necessary bitstream optimized for Menta's eFPGA architecture. This tool eliminates the need for additional FPGA configuration utilities, facilitating an effortless design flow. Customers can seamlessly integrate the programmer in SoC designs, benefiting from end-to-end configuration capabilities. With comprehensive support for RTL written in VHDL, Verilog, and SystemVerilog, Origami Programmer ensures seamless adaptation across various design constraints and advanced static timing analysis. It showcases a streamlined interface and enhanced scripting capabilities in TCL, catering to both standalone operations and API integrations. By supporting Linux platforms, it encompasses a broad range of applications from basic design trials to more complex field applications, promising rapid performance assessments and precise design configurations.
Calcite Core-hub is a dynamic processor core solution crafted to optimize performance for a wide range of applications. Building on the strengths of RISC-V architecture, Calcite Core-hub integrates advanced features that facilitate efficient computation and adaptable configuration, enabling developers to tailor functionalities to meet diverse project requirements. This core is designed to simplify the chip design process by providing a robust and scalable foundation that supports various applications, from IoT developments to high-performance computing tasks. Its configuration capabilities allow for precise adjustments in the ISA and microarchitecture, promoting innovation and custom design opportunities. InCore's Calcite Core-hub embodies the company's commitment to providing agile and versatile processor solutions that address modern technological challenges. By offering a modular approach to chip design, Calcite ensures developers can achieve their design objectives with flexibility and precision, making it a valuable resource in the semiconductor industry.
The BA51 is an ultra-low-power RISC-V processor designed for embedded applications that demand minimal power consumption. Employing a compact design starting at 16k gates, it operates with a single-issue, two-stage pipeline that effectively minimizes energy use while maintaining performance. The processor also supports additional power management features like dynamic clock gating, making it a perfect choice for battery-operated devices and other power-sensitive environments.
Grayskull represents Tenstorrent's solution for scalable, powerful computing in the AI domain. Designed to handle intensive AI workloads, this processor is built on a robust architecture that supports high throughput and data integrity under demanding conditions. The Grayskull's architecture allows for dynamic workload management and resource allocation, maximizing computing efficiency across a variety of tasks. It supports a wide range of data formats and computing paradigms, providing flexibility and adaptability to developers. This versatility helps in optimizing performance for specific workloads, enhancing overall computational throughput. Through intelligent design, Grayskull ensures seamless scalability, crucial for expanding IT infrastructures. It incorporates advanced communication protocols to deal effectively with intra-system data transmission, thus reducing latency and improving system responsiveness under heavy computing loads. Moreover, its integration capabilities enable it to mesh easily with existing systems, reducing deployment time and increasing ROI for enterprises. Tenstorrent's Grayskull is integral for those wishing to explore new possibilities in AI research and deployment. By offering an architecture designed from the ground up for AI tasks, it helps organizations innovate rapidly and respond to changing tech landscapes without the need to overhaul their hardware investments.
The Y90-180 offers a high-performance variant of the Zilog Z80180 design, featuring approximately 18K gates. It effectively enhances the functionalities of its predecessors, providing a robust execution environment tailored for intensive computational tasks. By amplifying the original architecture, it ensures reliable, high-speed processing capability for systems requiring the sophistication of a higher gate count within Zilog's ecosystem.
The Akida1000 Reference SoC represents BrainChip’s effort to provide a complete, event domain neural processing solution. This standalone device features comprehensive AI functionalities, supporting a vast network of 1.2 million neurons and 10 billion synapses. It is versatile in use, functioning independently or as a supportive co-processor across various applications, significantly improving edge AI deployment. BrainChip has integrated this SoC into reference development systems like Akida PCIe and Raspberry Pi, enabling working prototypes and AI system evaluations. Predominantly focused on efficient event-based computing, Akida1000 facilitates few-shot learning on-chip, which is critical for devices needing rapid personalization and adaptation without cloud reliance. Configuration flexibility allows seamless integration into diverse system architectures, backed by MetaTF tools that optimize design and deployment processes. Akida1000’s design ensures that neural processing remains power-efficient while maintaining high performance, critical for upcoming AI-driven smart device landscapes in consumer and IoT domains.
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