Tesla’s Ambitious Quest for Full Self-Driving
Tesla has been a pioneer in the electric vehicle (EV) industry, but its ambitions don’t stop there. The American automaker is investing heavily in AI infrastructure to achieve full self-driving (FSD) capabilities. The latest addition to this endeavor is a 10,000 GPU compute cluster, which came online recently. This system aims to process the massive amounts of data collected by Tesla vehicles to speed up the development of FSD features.
The Investment in Dojo Supercomputer
Tesla’s CEO, Elon Musk, is no stranger to making bold investments. The company plans to invest $1 billion in its Dojo supercomputer by the end of 2024. This AI supercomputer is designed to accelerate the development of Tesla’s autonomous driving software. It uses Tesla’s proprietary 15kW Dojo Training tiles, which are made up of D1 chip dies designed by Tesla and manufactured by TSMC.
Why GPUs are Crucial for Tesla
Tesla has been using GPUs in its infrastructure for years. In 2021, the company deployed a cluster of 720 GPU nodes, each equipped with eight A100 accelerators, totaling 5,760 GPUs. This system offered up to 1.8 exaFLOPS of FP16 performance. The latest deployment is almost double in size and utilizes Nvidia’s newest H100 GPUs, which offer three times the FP16 performance of their predecessors.
The Nvidia Connection
Elon Musk has openly stated that Tesla would take as many GPUs as Nvidia could deliver. The latest deployment uses Nvidia’s H100 GPUs, which offer significant performance gains over their predecessors. These GPUs also support FP8 math, which provides almost four petaFLOPS of peak performance.
On-Premises vs. Cloud
Tesla is not just renting GPUs from cloud providers like Microsoft or Google. The entire system is housed on-premises at Tesla’s facilities. Owning and maintaining the hardware gives Tesla full control, allowing for vertical integration, which is a significant advantage in the fast-paced tech world.
Datacenter Expansion Plans
Tesla is also looking to expand its datacenter footprint. A recent job posting suggests that the company is planning to build first-of-its-kind datacenters, which could potentially house additional capacity for its AI supercomputers.
Performance Metrics
The new system is expected to offer 39.5 exaFLOPS of FP8 performance and is supported by a hot tier cache capacity of more than 200 petabytes. These numbers are staggering and indicate the scale at which Tesla is operating.
The Road Ahead
While Tesla has been teasing FSD capabilities since 2016, the investments in AI infrastructure indicate a serious commitment to making it a reality. The new GPU cluster and the Dojo supercomputer are significant steps in this direction.
Conclusion
Tesla’s investment in a 10,000 GPU compute cluster and its ongoing work on the Dojo supercomputer are clear indicators of the company’s commitment to achieving full self-driving capabilities. With massive computational power and a focus on vertical integration, Tesla is well-positioned to make significant advancements in the field of autonomous driving.
FAQs
1. What is Tesla’s latest investment in AI?
Tesla has invested in a 10,000 GPU compute cluster to accelerate the development of its full self-driving capabilities.
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2. How is Tesla’s Dojo supercomputer different?
The Dojo supercomputer uses Tesla’s proprietary 15kW Dojo Training tiles and is designed to speed up the development of autonomous driving software.
3. Why is Tesla using Nvidia’s GPUs?
Nvidia’s latest H100 GPUs offer significant performance gains, making them ideal for Tesla’s needs.
4. Is Tesla using cloud-based solutions for its AI infrastructure?
No, Tesla houses its entire AI system on-premises, allowing for full control and vertical integration.
5. What are Tesla’s future plans for datacenters?
Tesla is looking to expand its datacenter footprint and recently posted a job opening for a senior engineering program manager for datacenters.
