Cublaslt Grouped Gemm -

cublasLtGroupedMatmulPlan_t groupPlans[3]; for (int i = 0; i < groupCount; i++) { cublasLtGroupedMatmulPlanInit(handle, matmulDesc, &groupPlans[i], CUDA_R_16F, CUDA_R_16F, CUDA_R_16F, CUDA_R_32F, m_arr[i], n, k); }

float alpha = 1.0f, beta = 0.0f; cublasLtMatmulGrouped(handle, nullptr, matmulDesc, &alpha, &beta, (void**)A_ptrs, (void**)B_ptrs, (void**)C_ptrs, (void**)C_ptrs, groupCount, groupPlans); cuBLASLt Grouped GEMM represents a paradigm shift for batched linear algebra on GPUs. It acknowledges that real-world workloads are irregular, heterogeneous, and dynamic. By moving the complexity of scheduling and fusing into the library, it allows developers to write clean, expressive code that still achieves near-peak hardware performance. cublaslt grouped gemm

cublasLtMatmulDesc_t matmulDesc; cublasLtMatmulDescCreate(&matmulDesc, CUDA_R_32F, CUDA_R_16F); cublasLtGroupedMatmulPlan_t groupPlans[3]; for (int i = 0; i