key=['M','N','K'], ) img 当我们去调整对应的调优空间 @triton.autotune( configs=[ triton.Config({'BLOCK_SIZE_M':32,'BLOCK_SIZE_N':64,'BLOCK_SIZE_K':32,'GROUP_SIZE_M':8},num_stages=5,num_warps=2), ], key=['M','N','K'], ) img
Config({'BLOCK_SIZE_M': 32, 'BLOCK_SIZE_N': 64, 'BLOCK_SIZE_K': 32, 'GROUP_SIZE_M': 8}, num_stages=5, num_warps=2), ], key=['M', 'N', 'K'], # 自动调优关键字 ) @triton.jit def matmul_kernel( # 指向矩阵的指针 a_ptr, b_ptr, c_ptr, # 矩阵维度 M, N, K, ...
g., `num_warps`) to try # - An auto-tuning *key* whose change in values will trigger evaluation of all the # provided configs @triton.autotune( configs=[ triton.Config({'BLOCK_SIZE_M': 128, 'BLOCK_SIZE_N': 256, 'BLOCK_SIZE_K': 64, 'GROUP_SIZE_M': 8}, num_stages=3, num...
单元测试的编写就显而易见了,为的是比较通过Triton生成的代码和通过pytorch的torch.mm算出的结果是否对齐 torch.manual_seed(0)a=torch.randn((512,512),device='cuda',dtype=torch.float16)b=torch.randn((512,512),device='cuda',dtype=torch.float16)triton_output=matmul(a,b)torch_output=torch.matmul(...
威猛 Triton SLA en 使用手册说明书 Translation of the original instructions Triton SLA English Triton SLA
A key feature of Triton is its support for multiple model execution modes, including dynamic batching, concurrent model execution, and multi-GPU inferencing. These capabilities allow organizations to efficiently serve AI models at scale, reducing latency and optimizing throughput. Trito...
MANUAL_MC_TAPE - All of the machine code program samples from the manual MANUAL_BASIC_TAPE - All of the BASIC program samples from the manual TRAIN_TAPE - Train graphics demonstration program "Although it is quite easy to use the VDU function within TRITON'S BASIC to produce moving graphics...
NVIDIA Triton Inference Server isseamlessly integrated in Azure Machine Learning managed online endpointsas a production release branch that provides monthly patches and bug fixes with a nine-month lifespan and can be deployed without manual code. It is also availabl...
The keyboard is backlit, with each key having its own LED. The software allows you to change the color of each key, similar to what Razer, Aorus and MSI currently do. I find the backlighting to be very even and subtle, similar to how it looks on the Razer Blade. There are some pre...
auto key = std::make_pair(op.getSrc().getType().getShape(), op.getSrc().getType().getElementType()); auto it = allocs.find(key); if (it != allocs.end()) { storeToAlloc[op] = it->second; continue; } storeToAlloc[op] = createAlloc(forOp, op); allocs[key] = storeTo...