whn09 ed49792a0c Add AWS Trainium (Neuron) platform, basic mode — part 1 ... Run DeepInfer on the native torch-neuronx device (PrivateUse1 `neuron`, torch-neuronx 2.14, no torch-xla), following the Ascend port's structure. - deep_cluster: Neuron discovery (one DeepInfer device = one logical NeuronCore, NEURON_RT_VISIBLE_CORES, NUMA from neuron-ls). - PlatformNeuron: takes the Ascend (is_npu) kernel layouts, adds is_neuron; DEEPINFER_NEURON_DEVICE=cpu runs the same code on the host for correctness work. - neuron_ops/transfer_to_neuron: map "cuda" devices, torch.device and torch.cuda.* onto neuron:0 (counterpart of torch_npu transfer_to_npu). - C++ extension: -DWITH_NEURON host-only build; torch-allocated buffers and tensor-view slot copies instead of raw device-pointer copies. - Pure-torch drop-in vendor packages (Ascend API semantics): deep_gemm, flash_mla, deep_select, tile_kernels, tilelang (constants only). - tilelang_ops/neuron backend: KV cache / metadata / norm / compress kernels; CP, ZOS and VL entry points raise NotImplementedError. - Basic mode defaults on Neuron: eager, no DSpark/MTP drafting, no zero-overhead scheduling; MoE avoids the GPU-only mega kernel; mHC prenorm GEMM uses the Ascend single-split reduction. Not yet included: deep_ep, the sampling kernels, end-to-end harness. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>		2026-10-20 18:34:51 +08:00
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__init__.py	initial commit	2026-10-20 12:09:42 +08:00
ascend.py	initial commit	2026-10-20 12:09:42 +08:00
cpu.py	initial commit	2026-10-20 12:09:42 +08:00
device.py	Add AWS Trainium (Neuron) platform, basic mode — part 1	2026-10-20 18:34:51 +08:00
neuron.py	Add AWS Trainium (Neuron) platform, basic mode — part 1	2026-10-20 18:34:51 +08:00
nvidia.py	initial commit	2026-10-20 12:09:42 +08:00