Cockpit-Driving Integration: Qualcomm SA8775 Chip Technical Analysis
The Qualcomm SA8775 chip is an integrated solution targeting intelligent cockpit and Advanced Driver Assistance Systems (ADAS), combining both functions in a single architecture. With up to 70 TOPS of computing power, it can handle both cockpit and basic intelligent driving requirements, offering significant cost and functional benefits for vehicle manufacturers and Tier 1 suppliers.
This article provides an in-depth analysis of Qualcomm SA8775’s technical features, solution details, and implementation considerations, exploring the chip’s potential and challenges in the intelligent cockpit and autonomous driving domains.
Part 1: Qualcomm’s Cockpit-Driving Integration Strategy and SA8775 Chip
The Qualcomm SA8775 chip is positioned for high-end intelligent driving and in-vehicle infotainment system integration, representing a unified cockpit-driving solution.
By supporting both digital cockpit and intelligent driving functions with a single SoC, it provides an integrated, high-performance solution for automobiles, meeting the industry’s needs for intelligence and connectivity while enhancing user experience while reducing costs and system complexity.
Its design goal is to simplify hardware architecture and lower development costs for domain controllers by integrating intelligent cockpit with autonomous driving capabilities.
Compared to traditional separated cockpit-driving architectures, this chip solution can save manufacturers thousands of yuan in costs. This architecture not only reduces vehicle wiring and hardware complexity but also enables innovation in automotive electrical and electronic architectures.
Core Positioning Includes:
- Targeting mid- to high-end automotive markets, supporting L2+ and L3 level autonomous driving
- Strengthening computing power allocation between intelligent cockpit and autonomous driving modules
- Providing modular design flexibility to adapt to diverse automotive manufacturer requirements
Key Parameters and Features:
CPU Performance
Adopts a two-cluster, eight-core design architecture, including Kryo 680 Gold Prime cores based on ARM Cortex-X1 architecture with a clock speed up to 2.35GHz, delivering powerful 230kDMIPS computing capability. Large L3 cache (4MB) and L2 cache (512kB) effectively improve processing speed and data throughput, performing excellently in multi-tasking and high-concurrency computing, meeting the needs of complex computational scenarios.
GPU Performance
Equipped with an Adreno 663 graphics processing unit with computing power between 1.1-1.3 TFLOPS, it offers powerful capabilities in graphics rendering, deep learning acceleration, and parallel computing. This provides strong support for high-quality image and video processing, autonomous driving perception, and other tasks, ensuring smooth visual experiences such as 8K ultra-high-definition displays and immersive 3D real-time rendering.
AI Acceleration
Employs Qualcomm’s V73 architecture with four built-in HVX vector extension units and two HMX matrix extension units, with a maximum frequency of 1.5GHz, specifically optimized for AI and deep learning inference performance, efficiently processing complex neural network models.
Additionally, the 8MB tightly-coupled VCTM cache provides more efficient storage support for AI acceleration, further improving inference processing speed, suitable for image processing and object recognition tasks in autonomous driving and intelligent driving assistance systems.
DSP and Security
Equipped with two general-purpose DSPs with a maximum frequency of 1.708GHz and 1MB L2 cache, capable of processing various digital signal processing tasks. Simultaneously, it integrates a 4-core ARM Cortex-R52 security island for handling critical security tasks such as encryption and authentication, complying with ASIL-D standards and effectively addressing risks of external attacks or data leaks, ensuring system security.
Memory Bandwidth
Supports LPDDR5 memory running at 3200MHz with a bandwidth of approximately 77GB/s. High-bandwidth memory enables faster data reading and writing, ensuring smooth execution of high-performance computing tasks and meeting the demands of processing large amounts of real-time data, images, and video streams, which is particularly crucial in data-intensive applications.
Power Consumption and Efficiency
Focuses on low-power design with a power consumption of 45W, providing stable operation for extended periods while maintaining high performance, suitable for embedded systems and automotive applications that require long-running operation with strict power requirements, achieving a good balance between performance and power consumption.
Part 2: SA8775 Solution Details
The core design of SA8775 focuses on optimizing computing power allocation between intelligent cockpit and autonomous driving domains.
Of the total 70 TOPS computing power, approximately 30-35 TOPS are dedicated to autonomous driving, with the remainder allocated to the intelligent cockpit. This distribution balances ADAS functionality with rich in-vehicle infotainment experiences.
Leveraging the Adreno 663 GPU and Qualcomm V73 architecture, the intelligent cockpit can achieve high-resolution displays, multi-tasking operations, and voice interaction capabilities. This module also supports multi-screen interaction, enhancing the driving and passenger experience.
The SA8775 can handle L2+ and some L3 level autonomous driving tasks, including environmental perception, path planning, and vehicle control. Its AI acceleration units are particularly suitable for processing data generated by cameras, LiDAR, and ultrasonic sensors, providing high-precision object recognition and decision support.
The security island module’s design ensures the system can maintain minimal functionality even when some functions fail, complying with ISO 26262 standards.
Cortex-R52 Based Processor Design Features for System Reliability and Performance Optimization:
Built-in Self-Test (BIST) and Security Monitoring
Features real-time monitoring and safe exit mechanisms, supporting debugging through JTAG interface.
Communication Interfaces
Utilizes UART/SPI interfaces for communication with external devices.
8-Core Architecture
- 4 Kryo Gold Prime cores (2.2 GHz) suitable for high-load tasks
- 4 Kryo Gold cores designed for low-power requirements
AI Acceleration
Dual Hexagon Tensor accelerators support efficient AI inference, including dynamic quantization and low-precision computing.
Memory Subsystem
LPDDR5, 6400 Mbps, 32-bit dual-channel, maximum 16 GB capacity, with 3 MB system cache and ECC functionality.
Image Processing
Qualcomm Spectra 680 ISP and Adreno VPU 670 GPU, supporting multi-camera data processing and efficient graphics rendering.
Display Output
Supports 8K resolution and VESA DSC technology.
Supports DPHY 1.2 and CPHY 1.2 standards, meeting high-resolution video data transmission requirements.
CPHY 1.2 parallel interface supports up to 3.5Gbps bandwidth per channel, while DPHY 1.2 serial interface supports transmission rates up to 2.5 Gbps. Supports multi-channel parallel transmission, increasing throughput, with Timing modules managing image signal timing to ensure camera module stability.
Communication Protocols
Supports various high-speed communication protocols, including:
- PCIe Gen 4 x4 providing bandwidth up to 16 GT/s, suitable for high-speed data transfer
- SGMII supporting high-speed network connections
- SerDes supporting efficient serial communication, typically used for high-speed video data transmission
- USB 3.0 supporting 5 Gbps transmission rates, suitable for connecting various external devices
- CAN FD specifically designed for vehicle networks, supporting higher data transmission rates, meeting vehicle system requirements for communication bandwidth and data integrity
The SA8775’s power consumption is relatively low, but as autonomous driving systems evolve toward higher computing capabilities and more complex scenarios, power consumption may become a limiting factor.
When designing systems, thermal solutions must be fully considered, such as employing heat pipe + graphite sheet composite cooling solutions to ensure stable chip operation even in high-temperature environments. Simultaneously, machine learning-based load prediction algorithms can be introduced to adjust the chip’s working mode in real-time according to application scenarios, achieving optimal balance between performance and power consumption.
To sum up
As a high-performance, multi-functional chip, the Qualcomm SA8775 demonstrates tremendous advantages and potential in cockpit-driving integrated applications. Its powerful CPU, GPU, and AI acceleration capabilities, comprehensive security mechanisms, and rich interfaces make it an ideal choice for intelligent driving and in-vehicle infotainment systems.
