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March 19, 2026cs.LGcs.AIAdvanced
SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits
Edward Lin, Sahil Modi, Siva Kumar Sastry Hari, Qijing Huang, Zhifan Ye, Nestor Qin, Fengzhe Zhou, Yuan Zhang, Jingquan Wang, Sana Damani, Dheeraj Peri, Ouye Xie, Aditya Kane, Moshe Maor, Michael Behar, Triston Cao, Rishabh Mehta, Vartika Singh, Vikram Sharma Mailthody, Terry Chen, Zihao Ye, Hanfeng Chen, Tianqi Chen, Vinod Grover, Wei Chen, Wei Liu, Eric Chung, Luis Ceze, Roger Bringmann, Cyril Zeller, Michael Lightstone, Christos Kozyrakis, Humphrey Shi
AI-Generated Summary
SOL-ExecBench is a new benchmark for evaluating AI systems that optimize GPU kernels by measuring how close they get to the theoretical maximum performance (Speed-of-Light) that the hardware can achieve, rather than just comparing against other software implementations. It includes 235 real optimization problems from actual AI models and uses a special pipeline called SOLAR to calculate what perfect performance would look like for each kernel. The benchmark includes safeguards to prevent cheating and focuses on modern NVIDIA Blackwell GPUs with various precision formats.
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Advanced
Categories
cs.LG, cs.AI
AI Tags
GPU optimizationbenchmarkingCUDA kernelsagentic AIhardware efficiencyperformance evaluationneural network inference