Open Source Summit North America 2025

Graphics Processing Units (GPUs) have become key to modern computing, enabling high-performance parallel processing beyond their original role in gaming. Today, they are critical for solving complex computational challenges effectively. To achieve high levels of parallelism, OpenCL is commonly used to break tasks into kernels, which are executed by multiple threads. Optimizing OpenCL performance on GPUs remains a persistent challenge, as it involves fine-tuning both software (OpenCL code, kernels) and hardware. One of the critical factors influencing GPU performance is the effective use of workgroups. The size of workgroups significantly impacts parallelism and efficiency.
This session focuses on key software optimizations in OpenCL, such as efficient memory management, kernel fusion and optimal workgroup sizing in improving GPU performance. We will demonstrate, how optimized OpenCL code can significantly enhance parallel execution and efficiency. This talk also addresses challenges faced by automotive GPUs, including power and thermal constraints with strategies to overcome these. Best practices for writing efficient OpenCL code tailored for automotive GPUs will also be outlined.