In the fast-evolving automotive world, high-performance computing (HPC) is the engine behind autonomous driving, digital twins, real-time simulations, and advanced vehicle design. The challenge lies in delivering lightning-fast data processing while keeping power use, heat, and hardware size in check.
Sharing the experience of Synopsis India, Sudeep Shivalli, Regional Senior Director, GTM of the company told Mobility Outlook that modern automotive HPC platforms combine CPUs, GPUs, and AI accelerators, assigning each task to the most efficient processor. Built on advanced semiconductor nodes like 7nm or 5nm, these chips pack high computing power with lower energy use and heat output. Processing data locally inside the vehicle—rather than sending it to the cloud—cuts latency, saves bandwidth, and enables instant responses.
With smart architectures, low-power chip designs, and effective cooling, automakers can push the boundaries of performance without exceeding a vehicle’s physical and energy limits—bringing the future of intelligent mobility within reach, he said.
According to Shivalli, a major hurdle in ADAS and in-vehicle infotainment (IVI) development is that software validation often starts only after hardware is ready, slowing progress. To speed things up without losing accuracy, the industry needs to move from traditional Hardware-in-the-Loop (HiL) testing to Software-in-the-Loop (SiL), allowing validation much earlier in the cycle. Scaling SiL across teams becomes easier with cloud-based virtualisation, which offers flexibility, faster collaboration, and the capacity to handle growing simulation workloads. “Synopsys is working with OEMs and Tier 1 suppliers to make this shift, cutting R&D time and costs while boosting efficiency,” he noted.
Scalable Hardware
Managing the massive volumes of sensor and training data for AI-driven vehicle development calls for scalable hardware that delivers ultra-low latency with optimal power, performance, and area (PPA). OEMs must decide whether to use off-the-shelf SoCs, design custom ones, or adopt a hybrid model, depending on their specific goals, he suggested. For custom designs, ensuring safety, reliability, quality, security, and power efficiency—especially for electric vehicles—is critical. As AI becomes a key competitive edge, many OEMs are also evaluating neural processing units (NPUs) and benchmarking them carefully to guide smart buy-or-build decisions.
Comprehensive Ecosystem
Ensuring ultra-low latency in safety-critical automotive edge AI means building systems with powerful processors, GPUs, and AI accelerators capable of high-speed data processing and complex algorithm execution. Synopsys supports this through a complete ecosystem of IP, tools, and platforms, including ASIL D-compliant solutions that meet the highest functional safety standards. Its ARC EV and NPX series are optimised for AI and machine learning inference, delivering high performance at ultra-low power and latency for applications like object detection and lane tracking. High-speed sensor integration is enabled through interfaces such as MIPI (Mobile Industry Processor Interface) CSI-2, Ethernet AVB, PCIe, and LPDDR (Low-Power Double Data Rate), ensuring rapid, low-latency communication between SoCs and advanced sensors like LiDAR and cameras.
According to Shivalli, scaling and integrating Edge AI and IoT across today’s diverse vehicle platforms is no easy task. Different hardware and software systems, varied sensors, and contrasting cost models make interoperability a challenge. The way forward lies in an ecosystem approach—adopting industry standards, modular architectures, and cloud integration—while shifting to software-defined vehicle platforms to simplify design and integration. Partner collaboration and over-the-air updates help maintain compatibility and ensure systems evolve with technology.
Addressing Cybersecurity
As connectivity grows, so do cybersecurity risks. Protecting vehicles requires strong security at both hardware and software levels. Synopsys addresses this with solutions that meet ISO 26262 for functional safety and ISO/SAE 21434 for cybersecurity. These include automotive-certified interfaces like MACsec (Media Access Control Security) and PCIe ( Peripheral Component Interconnect Express,), cryptographic tools such as random number generators and physical unclonable functions, and the tRoot hardware security subsystem—ensuring sensitive data and systems remain secure from end to end, he said.
India’s Strategic Ascent
Shivalli said that India’s semiconductor ambitions are being powered by a comprehensive government policy designed to build a robust domestic ecosystem. Recognising the complexity of chip fabrication, the strategy focuses on long-term global partnerships, gradual development of critical know-how, and steady investment in manufacturing infrastructure to close ecosystem gaps. The country already has a strong base in semiconductor design, and with major investments from Tata Electronics, CG Power, Kaynes, and HCL in fabs and OSAT facilities, India is fast building a complete value chain. Over the next two to three years, these moves are set to position the nation as a hub for fabs, OSATs, and product innovation.
Developing skilled talent is equally critical. In line with the MeitY C2S initiative, academia, research, and industry are being linked to train specialists in design and fabrication. Synopsys supports this effort through research fellowships, faculty training, curriculum development, student workshops, and hands-on chip design projects with foundries, helping to build deep technical expertise locally.
Attracting sustained investment into fabs—given their high capital needs and long gestation periods—requires both government backing and risk capital to fuel innovation. Investors are increasingly drawn to companies with a clear vision, differentiated products, and strong go-to-market strategies, particularly in strategic electronics, AI/HPC, automotive, and consumer electronics. As he put it, the focus must go beyond cost advantage to creating unique, value-driven solutions.
From a technology standpoint, Synopsys helps de-risk semiconductor projects with its end-to-end silicon-to-systems solutions, simulating factory environments and speeding up the path from design to mass production. Its offerings include TCAD for advanced process modelling, mask solutions for faster node development, manufacturing analytics for process optimisation, and silicon lifecycle management to monitor and enhance chip performance from design to deployment—empowering the industry to innovate with confidence and scale faster, Shivalli added.
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