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📖 NVIDIA cuBLASLt Developer Guide → Grouped GEMM section
Enter – a game changer for batched, variable-sized matmul operations. cublaslt grouped gemm documentation
Have you benchmarked grouped GEMM vs. batched GEMM for your use case? Let’s discuss below ⬇️ 📖 NVIDIA cuBLASLt Developer Guide → Grouped GEMM
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. in LLM inference
🔍 The grouped GEMM interface allows you to execute a list of independent matrix multiplications in a single kernel launch , drastically reducing launch latency and improving GPU utilization.
#CUDA #cuBLASLt #GPUComputing #GEMM #LLM #PerformanceOptimization Would you like a shorter version for Twitter/X or a code snippet example to accompany this post?