Mobileye's System-on-Chip Delivers 2nd Generation Solution for Visual Recognition and Interpretation
EyeQ2™, Mobileye's System-on-Chip (SoC) delivers a 2nd generation solution for computationally intensive applications for real-time visual recognition and scene interpretation and has cabin-grade automotive qualification for use in intelligent vehicle systems. The Mobileye EyeQ2™ reflects a new Philosophy of Vision based processing platform, includes optimal combination for Vision Scalar and Vector processing on a single die, based on Mobileye algorithm knowledge.
Mobileye EyeQ2™ will be launched in 2009 start of production involving a consolidated feature package with lanes, vehicles, pedestrian and fusion. Manufactured by STMicroelectronics, the concept behind the EyeQ2 is twofold:
- Mobileye EyeQ2™ is six times more powerful than the first generation Mobileye EyeQ™, thus allowing a higher degree of feature consolidation
- Mobileye EyQ2™ is multi-threaded thus allowing for an easier combination of different IPs, some from Mobileye and others from 3rd parties working in tandem with Mobileye software.
• Programmable ASIC
• Parallelism, 11 computing processors working simultaneously
• On chip 1M Byte of SRAM
• Vision application minded design
• Automotive qualified
The chip architecture is designed to run a full-fledged application on a single chip, and is completely programmable to accommodate a wide range of visual processing applications beyond automotive specific applications.
Mobileye EyeQ2™ is manufactured using the leading STMicroelectronics CMOS 90nm-micron technology, operating at 332Mhz. To optimize costp erformance, all peripheral interfaces are integrated in to the SoC, including dual CAN Controllers; dual UART, I2C, Mobile DDR SDRAM controller, parallel I/O, dual Video image data capture and video out units.
Mobileye’s SDK (System Development Kit) for Mobileye EyeQ2™ provides a well defined working environment for use by developers and programmers of applications based on the Mobileye EyeQ2™ SW and is highly suited also for inexperienced developers. Provided with Mobileye Vision algorithms as libraries.
The Mobileye EyeQ2™ architecture consists of two floating point, hyper-thread 64bit RISC 34KMIPS CPUs, five Vision Computing Engines (VCE), three Vector Microcode Processors (VMP™), Denali 64bit Mobile DDR Controller, 128bit internal Sonics Interconnect, dual 16bit Video input and 18bit Video output controllers, 16 channels DMA and several peripherals. The MIPS34K CPU manages the five VCEs, three VMP™ and the DMA, the second MIPS34K CPU and the multi-channel DMA as well as the other Peripherals. The five VCEs, three VMP™ and the MIPS34K CPU perform all the intensive vision computations required by the applications such as tracking and pattern classification.
|
Related News
- TI Delivers Industry's First Sub-1 GHz RF System-on-Chip with Integrated USB Controller for Wireless Sensor Networks
- AMCC Delivers Highly Integrated, Security-Enabled System-on-Chip, Offering Low-Power and Low-Cost Benefits to Customers; AMCC's PowerPC(R) 440EPx Commences Sampling
- Chipcon Delivers on World's First True System-on-Chip (SoC) ZigBee(TM) Solution
- MediaTek and TSMC Unveil the World's First 7nm 8K Resolution Digital TV System-on-Chip
- Arteris IP Completes Acquisition of Magillem Design Services Assets, Creating World's Premier System-on-Chip Integration Company
Breaking News
- RISC-V International Promotes Andrea Gallo to CEO
- See the 2025 Best Edge AI Processor IP at the Embedded Vision Summit
- Andes Technology Showcases RISC-V AI Leadership at RISC-V Summit Europe 2025
- RISC-V Royalty-Driven Revenue to Exceed License Revenue by 2027
- Keysom Unveils Keysom Core Explorer V1.0
Most Popular
- RISC-V International Promotes Andrea Gallo to CEO
- See the 2025 Best Edge AI Processor IP at the Embedded Vision Summit
- Andes Technology Showcases RISC-V AI Leadership at RISC-V Summit Europe 2025
- Ceva, Inc. Announces First Quarter 2025 Financial Results
- Cadence Unveils Millennium M2000 Supercomputer with NVIDIA Blackwell Systems to Transform AI-Driven Silicon, Systems and Drug Design
![]() |
E-mail This Article | ![]() |
![]() |
Printer-Friendly Page |