If you're working with (e.g., in LLM inference, attention mechanisms, or recommendation systems), you’ve likely hit the overhead of launching many separate GEMM kernels.
Enter – a game changer for batched, variable-sized matmul operations. cublaslt grouped gemm documentation
#CUDA #cuBLASLt #GPUComputing #GEMM #LLM #PerformanceOptimization Would you like a shorter version for Twitter/X or a code snippet example to accompany this post? If you're working with (e
Have you benchmarked grouped GEMM vs. batched GEMM for your use case? Let’s discuss below ⬇️ If you're working with (e.g.
📖 NVIDIA cuBLASLt Developer Guide → Grouped GEMM section
