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"domain": "com.microsoft",
"name": "QMoE",
"sinceVersion": 1,
"description": "Quantized mixture of experts over float32 activations and raw uint8-packed integer expert weights. The package implements 4- and 8-bit symmetric dequantization, ReLU, and interleaved SwiGLU for rank-2 or rank-3 input. Routing uses the softmax over the selected top-k logits, matching ONNX Runtime QMoE when the omitted `router_weights` input is absent. Biases, explicit zero points, FC3, sparse mixing, provider-prepacked layouts, and FP4/FP8 modes are not implemented.",
"inputs": [
{
"role": "input",
"dtype": "T",
"description": "Token activations of shape `(num_tokens, hidden_size)` or `(batch_size, sequence_length, hidden_size)`."
},
{
"role": "router_probs",
"dtype": "T",
"rank": 2,
"description": "Routing logits of shape `(num_tokens, num_experts)`, where `num_tokens` is the product of the leading input dimensions."
},
{
"role": "fc1_experts_weights",
"dtype": "T1",
"rank": 3,
"description": "Raw packed FC1 weights of shape `(num_experts, fusion_size * inter_size, hidden_size / pack_size)`, where `fusion_size` is 2 only for interleaved SwiGLU and `pack_size` is 2 for 4-bit or 1 for 8-bit weights."
},
{
"role": "fc1_scales",
"dtype": "T2",
"description": "Required FC1 dequantization scales: rank 2 `(num_experts, fusion_size * inter_size)` for column-wise quantization, or rank 3 with a trailing `hidden_size / block_size` axis."
},
{
"role": "fc2_experts_weights",
"dtype": "T1",
"rank": 3,
"description": "Raw packed FC2 weights of shape `(num_experts, hidden_size, inter_size / pack_size)`."
},
{
"role": "fc2_scales",
"dtype": "T2",
"description": "Required FC2 dequantization scales: rank 2 `(num_experts, hidden_size)` for column-wise quantization, or rank 3 with a trailing `inter_size / block_size` axis."
}
],
"outputs": [
{
"role": "output",
"dtype": "T",
"shape": "shapes.input",
"description": "Routed expert output with the same shape as `input`."
}
],
"attributes": {
"activation_alpha": 1,
"activation_beta": 0,
"activation_type": "relu",
"expert_weight_bits": 4,
"k": 1,
"normalize_routing_weights": 0,
"quant_type": "int",
"swiglu_fusion": 0,
"use_sparse_mixer": 0,
"weights_prepacked": -1
},
"attributeDescriptions": {
"activation_alpha": "Alpha used by SwiGLU; the exact standard default is 1.",
"activation_beta": "Beta added to the SwiGLU linear branch; the exact standard default is 0.",
"activation_type": "Activation applied after FC1. This package supports `relu` and `swiglu`; the exact standard default is `relu`.",
"block_size": "Optional quantization block size along the reduction dimension. Omission selects column-wise scaling; a supplied value must be a power of two of at least 16 and divide both `hidden_size` and `inter_size`.",
"expert_weight_bits": "Integer expert-weight bit width. This package supports 4 and 8; the exact standard default is 4.",
"k": "Number of experts selected per token; the exact standard default is 1.",
"normalize_routing_weights": "Accepted values are 0 and 1. With the separate `router_weights` input omitted, ONNX Runtime QMoE applies a softmax over the selected top-k logits for either value; the attribute only distinguishes the unsupported separate-weight path.",
"quant_type": "Quantization family. This package supports only the exact standard default `int`.",
"swiglu_fusion": "SwiGLU packing mode. ReLU uses the exact standard default 0; supported SwiGLU interleaves gate/up FC1 rows with value 1.",
"swiglu_limit": "Optional SwiGLU clamp limit. Omission means no finite clamp.",
"use_sparse_mixer": "Whether to use sparse-mixer routing. The exact standard default and only supported value is 0.",
"weights_prepacked": "Provider weight-layout selector. Values -1 and 0 both consume the public raw packed tensor layout; provider-specific prepacked value 1 is not portable and is rejected."
},
"attributeConstraints": {
"activation_type": { "values": ["relu", "swiglu"] },
"expert_weight_bits": { "values": [4, 8] },
"normalize_routing_weights": { "values": [0, 1] },
"quant_type": { "values": ["int"] },
"swiglu_fusion": { "values": [0, 1] },
"use_sparse_mixer": { "values": [0] },
"weights_prepacked": { "values": [-1, 0] }
},
"typeConstraints": { "T": ["float32"], "T1": ["uint8"], "T2": ["float32"] },
"args": {
"inputT": { "kind": "tensor", "semantic": "input", "role": "input" },
"routerT": { "kind": "tensor", "semantic": "router_probs", "role": "input" },
"fc1T": { "kind": "tensor", "semantic": "fc1_experts_weights", "role": "input" },
"fc1ScalesT": { "kind": "tensor", "semantic": "fc1_scales", "role": "input" },
"fc2T": { "kind": "tensor", "semantic": "fc2_experts_weights", "role": "input" },
"fc2ScalesT": { "kind": "tensor", "semantic": "fc2_scales", "role": "input" },
"outputT": { "kind": "tensor", "semantic": "output", "role": "output" }
},
"tunables": {
"workgroupSize": 64,
"decodeLanes": 32,
"decodeBlockTarget": 1024,
"decodeMinLaneTrips": 4,
"groupThreads": 8,
"groupRegM": 4,
"groupRegN": 4,
"groupTileK": 16,
"groupRouteWorkgroup": 256
},
"derive": {
"deviceWorkgroupCap": "min(device.limits.maxComputeInvocationsPerWorkgroup, device.limits.maxComputeWorkgroupSizeX)",
"wave32Adapter": "has(device.adapterInfo, \"subgroupMinSize\") and has(device.adapterInfo, \"subgroupMaxSize\") and device.adapterInfo.subgroupMinSize == 32 and device.adapterInfo.subgroupMaxSize == 32",
"canPinSubgroupSize32": "device.features.has(\"subgroups\") and device.features.has(\"subgroup-size-control\") and has(device.adapterInfo, \"subgroupMinSize\") and has(device.adapterInfo, \"subgroupMaxSize\") and device.adapterInfo.subgroupMinSize <= 32 and device.adapterInfo.subgroupMaxSize >= 32",
"pinSubgroupSize32": "canPinSubgroupSize32 and not wave32Adapter",
"wave32Effective": "wave32Adapter or pinSubgroupSize32",
"hiddenSize": "dim(shapes.input, ranks.input - 1)",
"numTokens": "numel(shapes.input) / max(1, hiddenSize)",
"topK": "attrs.k",
"weightBits": "attrs.expert_weight_bits",
"quantBlockSize": "attrs.block_size if has(attrs, \"block_size\") else 0",
"packSize": "2 if weightBits == 4 else 1",
"quantMidpoint": "8 if weightBits == 4 else 128",
"fusionSize": "2 if attrs.activation_type == \"swiglu\" and attrs.swiglu_fusion == 1 else 1",
"interSize": "dim(shapes.fc1_experts_weights, 1) / fusionSize",
"fc1PackedCols": "dim(shapes.fc1_experts_weights, 2)",
"fc2PackedCols": "dim(shapes.fc2_experts_weights, 2)",
"colWiseScales": "quantBlockSize == 0",
"fc1ScaleBlocks": "1 if colWiseScales else hiddenSize / max(1, quantBlockSize)",
"fc2ScaleBlocks": "1 if colWiseScales else interSize / max(1, quantBlockSize)",
"activationSupported": "(attrs.activation_type == \"relu\" and attrs.swiglu_fusion == 0) or (attrs.activation_type == \"swiglu\" and attrs.swiglu_fusion == 1)",
"routingModeSupported": "attrs.normalize_routing_weights == 0 or attrs.normalize_routing_weights == 1",
"rawWeightLayout": "attrs.weights_prepacked == -1 or attrs.weights_prepacked == 0",
"inputOutputShapeOk": "((ranks.input == 2 and ranks.output == 2 and dim(shapes.output, 0) == dim(shapes.input, 0) and dim(shapes.output, 1) == dim(shapes.input, 1)) or (ranks.input == 3 and ranks.output == 3 and dim(shapes.output, 0) == dim(shapes.input, 0) and dim(shapes.output, 1) == dim(shapes.input, 1) and dim(shapes.output, 2) == dim(shapes.input, 2))) and hiddenSize > 0",
"quantBlockSizeOk": "colWiseScales or (quantBlockSize >= 16 and pow2ceil(quantBlockSize) == quantBlockSize and hiddenSize % quantBlockSize == 0 and interSize % quantBlockSize == 0)",
"quantScalesOk": "tensorDtypes.fc1_scales == \"float32\" and tensorDtypes.fc2_scales == \"float32\" and dim(shapes.fc1_scales, 0) == dim(shapes.router_probs, 1) and dim(shapes.fc2_scales, 0) == dim(shapes.router_probs, 1) and dim(shapes.fc1_scales, 1) == dim(shapes.fc1_experts_weights, 1) and dim(shapes.fc2_scales, 1) == hiddenSize and ((ranks.fc1_scales == 2 and ranks.fc2_scales == 2) if colWiseScales else (ranks.fc1_scales == 3 and ranks.fc2_scales == 3 and dim(shapes.fc1_scales, 2) == fc1ScaleBlocks and dim(shapes.fc2_scales, 2) == fc2ScaleBlocks))",
"quantShapeOk": "inputOutputShapeOk and ranks.router_probs == 2 and ranks.fc1_experts_weights == 3 and ranks.fc2_experts_weights == 3 and dim(shapes.router_probs, 0) == numTokens and dim(shapes.fc1_experts_weights, 0) == dim(shapes.router_probs, 1) and dim(shapes.fc2_experts_weights, 0) == dim(shapes.router_probs, 1) and dim(shapes.fc1_experts_weights, 1) % fusionSize == 0 and dim(shapes.fc2_experts_weights, 1) == hiddenSize and dim(shapes.fc1_experts_weights, 2) * packSize == hiddenSize and dim(shapes.fc2_experts_weights, 2) * packSize == interSize and quantBlockSizeOk and quantScalesOk",
"quantContract": "activationSupported and routingModeSupported and rawWeightLayout and quantShapeOk and topK >= 1 and topK <= dim(shapes.router_probs, 1)",
"workgroupSizeOk": "tunables.workgroupSize >= 1 and tunables.workgroupSize <= deviceWorkgroupCap",
"hiddenChunkFits": "topK * interSize * 4 <= device.limits.maxStorageBufferBindingSize and topK * interSize * 4 <= device.limits.maxBufferSize",
"hiddenChunkTokens": "numTokens if interSize == 0 else min(numTokens, max(1, floor(min(device.limits.maxStorageBufferBindingSize, device.limits.maxBufferSize) / (topK * interSize * 4))))",
"hiddenChunkCount": "max(1, ceilDiv(numTokens, max(1, hiddenChunkTokens)))",
"routeScratchBytes": "numTokens * topK * 4",
"routedScratchFits": "routeScratchBytes <= device.limits.maxStorageBufferBindingSize and routeScratchBytes <= device.limits.maxBufferSize",
"groupTileM": "tunables.groupThreads * tunables.groupRegM",
"groupTileN": "tunables.groupThreads * tunables.groupRegN",
"groupTileKVec": "ceilDiv(tunables.groupTileK, 4)",
"groupThreadCount": "tunables.groupThreads * tunables.groupThreads",
"groupSlots": "hiddenChunkTokens * topK",
"groupMaxTiles": "ceilDiv(groupSlots, max(1, groupTileM)) + dim(shapes.router_probs, 1)",
"groupSharedBytes": "(groupTileM * tunables.groupTileK + 2 * groupTileN * tunables.groupTileK + groupTileM) * 4",
"groupSlotOutBytes": "hiddenChunkTokens * topK * hiddenSize * 4",
"groupedDeviceOk": "groupThreadCount <= device.limits.maxComputeInvocationsPerWorkgroup and tunables.groupThreads <= device.limits.maxComputeWorkgroupSizeX and tunables.groupThreads <= device.limits.maxComputeWorkgroupSizeY and tunables.groupRouteWorkgroup <= deviceWorkgroupCap and groupSharedBytes <= device.limits.maxComputeWorkgroupStorageSize and dim(shapes.router_probs, 1) * 8 <= device.limits.maxComputeWorkgroupStorageSize and tunables.groupTileK % 4 == 0",
"groupedDispatchOk": "groupMaxTiles <= device.limits.maxComputeWorkgroupsPerDimension and ceilDiv(interSize, max(1, groupTileN)) <= device.limits.maxComputeWorkgroupsPerDimension and ceilDiv(hiddenSize, max(1, groupTileN)) <= device.limits.maxComputeWorkgroupsPerDimension",
"groupSlotOutFits": "groupSlotOutBytes <= device.limits.maxStorageBufferBindingSize and groupSlotOutBytes <= device.limits.maxBufferSize",
"groupedShapeOk": "numTokens * topK * 4 >= groupTileM * dim(shapes.router_probs, 1)",
"groupedContract": "quantContract and workgroupSizeOk and hiddenChunkFits and routedScratchFits and interSize > 0 and groupedDeviceOk and groupedDispatchOk and groupSlotOutFits and groupedShapeOk",
"sgmatWorkgroup": "128",
"sgmatSubgroups": "4",
"sgmatRowSubtiles": "2",
"groupedSgmatSharedBytes": "groupTileM * 4 + groupTileM * 32 * 4 + 64 * 32 * 4 + sgmatSubgroups * 4 * 64 * 4",
"groupedSgmatOk": "groupedContract and groupTileM == 32 and interSize % 32 == 0 and groupedSgmatSharedBytes <= device.limits.maxComputeWorkgroupStorageSize and ceilDiv(hiddenSize, 64) <= device.limits.maxComputeWorkgroupsPerDimension and hiddenSize % 32 == 0",
"decodeLanesOk": "tunables.decodeLanes >= 1 and tunables.decodeLanes <= tunables.workgroupSize and tunables.workgroupSize % tunables.decodeLanes == 0",
"decodeRows": "max(1, tunables.workgroupSize / max(1, tunables.decodeLanes))",
"decodeDeviceOk": "workgroupSizeOk and decodeLanesOk and tunables.decodeLanes <= device.limits.maxComputeWorkgroupSizeX and decodeRows <= device.limits.maxComputeWorkgroupSizeY and tunables.workgroupSize * 8 <= device.limits.maxComputeWorkgroupStorageSize",
"decodeDispatchOk": "ceilDiv(interSize, decodeRows) <= device.limits.maxComputeWorkgroupsPerDimension and ceilDiv(hiddenSize, decodeRows) <= device.limits.maxComputeWorkgroupsPerDimension and hiddenChunkTokens * topK <= device.limits.maxComputeWorkgroupsPerDimension",
"decodeLaneDepth": "min(hiddenSize, interSize) / max(1, tunables.decodeLanes)",
"decodeDepthOk": "decodeLaneDepth >= tunables.decodeMinLaneTrips",
"splitFc1Blocks": "ceilDiv(numTokens * topK * interSize, max(1, tunables.workgroupSize))",
"decodeOccupancyOk": "splitFc1Blocks <= tunables.decodeBlockTarget",
"decodeContract": "quantContract and decodeDeviceOk and decodeDispatchOk and hiddenChunkFits and routedScratchFits and interSize > 0 and decodeDepthOk and (decodeOccupancyOk or not groupedContract)"
},
"constants": {
"tokens": "numTokens",
"hidden": "hiddenSize",
"experts": "dim(shapes.router_probs, 1)",
"fc1Rows": "dim(shapes.fc1_experts_weights, 1)",
"inter": "interSize",
"topK": "topK",
"workgroupSize": "tunables.workgroupSize",
"activationType": "attrs.activation_type",
"hasSwigluLimit": "has(attrs, \"swiglu_limit\")",
"swigluLimit": "attrs.swiglu_limit if has(attrs, \"swiglu_limit\") else 0",
"quantMidpoint": "quantMidpoint",
"quantBlockSize": "quantBlockSize",
"packSize": "packSize",
"fc1PackedCols": "fc1PackedCols",
"fc2PackedCols": "fc2PackedCols",
"colWiseScales": "colWiseScales",
"fc1ScaleBlocks": "fc1ScaleBlocks",
"fc2ScaleBlocks": "fc2ScaleBlocks"
},
"bindingSets": {
"route": [
{
"name": "router_probs",
"arg": "routerT",
"semantic": "router_probs",
"buffer": { "type": "read-only-storage" },
"elementType": "f32"
},
{ "name": "route_expert", "semantic": "routeExpert", "buffer": { "type": "storage" }, "elementType": "u32" },
{ "name": "route_mix", "semantic": "routeMix", "buffer": { "type": "storage" }, "elementType": "f32" }
],
"fc1Activation": [
{
"name": "input",
"arg": "inputT",
"semantic": "input",
"buffer": { "type": "read-only-storage" },
"elementType": "f32"
},
{
"name": "route_expert",
"semantic": "routeExpert",
"buffer": { "type": "read-only-storage" },
"elementType": "u32"
},
{
"name": "fc1_experts_weights",
"arg": "fc1T",
"semantic": "fc1_experts_weights",
"buffer": { "type": "read-only-storage" },
"elementType": "u32"
},
{
"name": "fc1_scales",
"arg": "fc1ScalesT",
"semantic": "fc1_scales",
"buffer": { "type": "read-only-storage" },
"elementType": "f32"
},
{ "name": "hidden_act", "semantic": "hiddenAct", "buffer": { "type": "storage" }, "elementType": "f32" },
{
"name": "params",
"semantic": "kernel.params",
"buffer": { "type": "uniform" },
"struct": {
"name": "Params",
"fields": [
{ "name": "activationAlpha", "type": "f32", "value": "attrs.activation_alpha" },
{ "name": "activationBeta", "type": "f32", "value": "attrs.activation_beta" },
{ "name": "tokenOffset", "type": "u32", "value": "repeat.chunk * hiddenChunkTokens" },
{
"name": "tokenCount",
"type": "u32",
"value": "min(hiddenChunkTokens, numTokens - repeat.chunk * hiddenChunkTokens)"
}
]
}
}
],
"output": [
{ "name": "hidden_act", "semantic": "hiddenAct", "buffer": { "type": "read-only-storage" }, "elementType": "f32" },
{
"name": "route_expert",
"semantic": "routeExpert",
"buffer": { "type": "read-only-storage" },
"elementType": "u32"
},
{ "name": "route_mix", "semantic": "routeMix", "buffer": { "type": "read-only-storage" }, "elementType": "f32" },
{
"name": "fc2_experts_weights",
"arg": "fc2T",
"semantic": "fc2_experts_weights",
"buffer": { "type": "read-only-storage" },
"elementType": "u32"
},
{
"name": "fc2_scales",
"arg": "fc2ScalesT",
"semantic": "fc2_scales",
"buffer": { "type": "read-only-storage" },
"elementType": "f32"
},
{
"name": "output",
"arg": "outputT",
"semantic": "output",
"buffer": { "type": "storage" },
"elementType": "f32"
},
{
"name": "params",
"semantic": "kernel.params",
"buffer": { "type": "uniform" },
"struct": {
"name": "Params",
"fields": [
{ "name": "tokenOffset", "type": "u32", "value": "repeat.chunk * hiddenChunkTokens" },
{
"name": "tokenCount",
"type": "u32",
"value": "min(hiddenChunkTokens, numTokens - repeat.chunk * hiddenChunkTokens)"
}
]
}
}
],
"zeroInterOutput": [
{
"name": "output",
"arg": "outputT",
"semantic": "output",
"buffer": { "type": "storage" },
"elementType": "f32"
}
],
"group": [
{
"name": "route_expert",
"semantic": "routeExpert",
"buffer": { "type": "read-only-storage" },
"elementType": "u32"
},
{ "name": "slot_list", "semantic": "slotList", "buffer": { "type": "storage" }, "elementType": "u32" },
{ "name": "tile_meta", "semantic": "tileMeta", "buffer": { "type": "storage" }, "elementType": "u32" },
{
"name": "params",
"semantic": "kernel.params",
"buffer": { "type": "uniform" },
"struct": {
"name": "Params",
"fields": [
{ "name": "tokenOffset", "type": "u32", "value": "repeat.chunk * hiddenChunkTokens" },
{
"name": "tokenCount",
"type": "u32",
"value": "min(hiddenChunkTokens, numTokens - repeat.chunk * hiddenChunkTokens)"
}
]
}
}
],
"fc1Grouped": [
{
"name": "input",
"arg": "inputT",
"semantic": "input",
"buffer": { "type": "read-only-storage" },
"elementType": "f32"
},
{ "name": "slot_list", "semantic": "slotList", "buffer": { "type": "read-only-storage" }, "elementType": "u32" },
{ "name": "tile_meta", "semantic": "tileMeta", "buffer": { "type": "read-only-storage" }, "elementType": "u32" },
{
"name": "fc1_experts_weights",
"arg": "fc1T",
"semantic": "fc1_experts_weights",
"buffer": { "type": "read-only-storage" },
"elementType": "u32"
},
{
"name": "fc1_scales",
"arg": "fc1ScalesT",
"semantic": "fc1_scales",
"buffer": { "type": "read-only-storage" },
"elementType": "f32"
},
{ "name": "hidden_act", "semantic": "hiddenAct", "buffer": { "type": "storage" }, "elementType": "f32" },
{
"name": "params",
"semantic": "kernel.params",
"buffer": { "type": "uniform" },
"struct": {
"name": "Params",
"fields": [
{ "name": "activationAlpha", "type": "f32", "value": "attrs.activation_alpha" },
{ "name": "activationBeta", "type": "f32", "value": "attrs.activation_beta" },
{ "name": "tokenOffset", "type": "u32", "value": "repeat.chunk * hiddenChunkTokens" }
]
}
}
],
"outputGrouped": [
{ "name": "hidden_act", "semantic": "hiddenAct", "buffer": { "type": "read-only-storage" }, "elementType": "f32" },
{ "name": "slot_list", "semantic": "slotList", "buffer": { "type": "read-only-storage" }, "elementType": "u32" },
{ "name": "tile_meta", "semantic": "tileMeta", "buffer": { "type": "read-only-storage" }, "elementType": "u32" },
{
"name": "fc2_experts_weights",
"arg": "fc2T",
"semantic": "fc2_experts_weights",
"buffer": { "type": "read-only-storage" },
"elementType": "u32"
},
{
"name": "fc2_scales",
"arg": "fc2ScalesT",
"semantic": "fc2_scales",
"buffer": { "type": "read-only-storage" },
"elementType": "f32"
},
{ "name": "slot_out", "semantic": "slotOut", "buffer": { "type": "storage" }, "elementType": "f32" }
],
"mix": [
{ "name": "slot_out", "semantic": "slotOut", "buffer": { "type": "read-only-storage" }, "elementType": "f32" },
{ "name": "route_mix", "semantic": "routeMix", "buffer": { "type": "read-only-storage" }, "elementType": "f32" },
{
"name": "output",
"arg": "outputT",
"semantic": "output",
"buffer": { "type": "storage" },
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},
{
"name": "params",
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"buffer": { "type": "uniform" },
"struct": {
"name": "Params",
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{ "name": "tokenOffset", "type": "u32", "value": "repeat.chunk * hiddenChunkTokens" },
{
"name": "tokenCount",
"type": "u32",
"value": "min(hiddenChunkTokens, numTokens - repeat.chunk * hiddenChunkTokens)"
}
]
}
}
],
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},
{
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},
{
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},
{
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},
{ "name": "hidden_act", "semantic": "hiddenAct", "buffer": { "type": "storage" }, "elementType": "f32" }
],
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},
{
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},
{
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},
{
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},
{ "name": "hidden_act", "semantic": "hiddenAct", "buffer": { "type": "storage" }, "elementType": "f32" },
{
"name": "params",
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"buffer": { "type": "uniform" },
"struct": {
"name": "Params",
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{ "name": "activationAlpha", "type": "f32", "value": "attrs.activation_alpha" },
{ "name": "activationBeta", "type": "f32", "value": "attrs.activation_beta" },
{ "name": "tokenOffset", "type": "u32", "value": "repeat.chunk * hiddenChunkTokens" }
]
}
}
],
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{
"name": "route_expert",
"semantic": "routeExpert",
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},
{ "name": "route_mix", "semantic": "routeMix", "buffer": { "type": "read-only-storage" }, "elementType": "f32" },
{
"name": "fc2_experts_weights",
"arg": "fc2T",
"semantic": "fc2_experts_weights",
"buffer": { "type": "read-only-storage" },
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},
{
"name": "fc2_scales",
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},
{
"name": "output",
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}
],
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{
"name": "route_expert",
"semantic": "routeExpert",
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},
{ "name": "route_mix", "semantic": "routeMix", "buffer": { "type": "read-only-storage" }, "elementType": "f32" },
{
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},
{
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},
{
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"buffer": { "type": "storage" },
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},
{
"name": "params",
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"struct": {
"name": "Params",
"fields": [{ "name": "tokenOffset", "type": "u32", "value": "repeat.chunk * hiddenChunkTokens" }]
}
}
]
},
"variants": [
{
"id": "quant_zero_inter",
"priority": 20,
"when": ["quantContract", "workgroupSizeOk", "interSize == 0"],
"passes": [
{
"id": "output_stage",
"name": "QMoE.OutputStageZeroInter",
"source": {
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"inputs": { "outputElementCount": "numel(shapes.output)" }
},
"bindings": "zeroInterOutput",
"dispatch": { "threads": "numel(shapes.output)", "workgroupSize": "constants.workgroupSize" }
}
]
},
{
"id": "quant_grouped_sgmat_routed",
"priority": 32,
"when": ["groupedSgmatOk", "wave32Effective"],
"constants": {
"groupTileM": "groupTileM",
"groupRouteWorkgroup": "tunables.groupRouteWorkgroup",
"sgmatWorkgroup": "sgmatWorkgroup",
"sgmatSubgroups": "sgmatSubgroups",
"sgmatRowSubtiles": "sgmatRowSubtiles"
},
"intermediates": [
{ "id": "routeExpert", "dtype": "uint32", "shape": "[numTokens * topK]" },
{ "id": "routeMix", "dtype": "float32", "shape": "[numTokens * topK]" },
{ "id": "hiddenAct", "dtype": "float32", "shape": "[hiddenChunkTokens * topK * interSize]" },
{ "id": "slotList", "dtype": "uint32", "shape": "[max(1, groupSlots)]" },
{ "id": "tileMeta", "dtype": "uint32", "shape": "[1 + 3 * groupMaxTiles]" },
{ "id": "slotOut", "dtype": "float32", "shape": "[max(1, hiddenChunkTokens * topK * hiddenSize)]" }
],
"passes": [
{
"id": "route_stage",
"name": "QMoE.RouteStage",
"shader": "qmoe-route-stage.wgsl.jinja",
"bindings": "route",
"dispatch": { "threads": "numTokens", "workgroupSize": "constants.workgroupSize" }
},
{
"id": "token_chunks",
"repeat": { "count": "hiddenChunkCount", "index": "chunk" },
"passes": [
{
"id": "group_stage",
"name": "QMoE.GroupStage",
"shader": "expert-group-slots.wgsl.jinja",
"bindings": "group",
"dispatch": {
"threads": "constants.groupRouteWorkgroup",
"workgroupSize": "constants.groupRouteWorkgroup"
}
},
{
"id": "fc1_activation_stage",
"name": "QMoE.FC1ActivationStageGroupedSgmat",
"shader": "qmoe-fc1-activation-grouped-sgmat.wgsl.jinja",
"bindings": "fc1Grouped",
"dispatch": { "x": "groupMaxTiles", "y": "ceilDiv(interSize * fusionSize, 64)" }
},
{
"id": "output_stage",
"name": "QMoE.OutputStageGroupedSgmat",
"shader": "qmoe-output-grouped-sgmat.wgsl.jinja",
"bindings": "outputGrouped",
"dispatch": { "x": "groupMaxTiles", "y": "ceilDiv(hiddenSize, 64)" }
},
{
"id": "mix_stage",
"name": "QMoE.MixStage",
"shader": "qmoe-mix-stage.wgsl.jinja",
"bindings": "mix",
"dispatch": {
"threads": "min(hiddenChunkTokens, numTokens - repeat.chunk * hiddenChunkTokens) * hiddenSize",
"workgroupSize": "constants.workgroupSize"
}
}
]
}
],
"requires": {
"features": ["subgroups", "chromium-experimental-subgroup-matrix"],
"limits": { "maxComputeWorkgroupStorageSize": 16512 },
"subgroupMatrixConfigs": [{ "componentType": "f32", "resultComponentType": "f32", "M": 8, "N": 8, "K": 8 }]
}
},
{
"id": "quant_grouped_routed",
"priority": 30,
"when": ["groupedContract"],
"constants": {
"groupTileM": "groupTileM",
"groupTileN": "groupTileN",
"groupTileK": "tunables.groupTileK",
"groupTileKVec": "groupTileKVec",
"groupThreads": "tunables.groupThreads",
"regM": "tunables.groupRegM",
"regN": "tunables.groupRegN",
"groupRouteWorkgroup": "tunables.groupRouteWorkgroup"
},
"intermediates": [
{ "id": "routeExpert", "dtype": "uint32", "shape": "[numTokens * topK]" },
{ "id": "routeMix", "dtype": "float32", "shape": "[numTokens * topK]" },
{ "id": "hiddenAct", "dtype": "float32", "shape": "[hiddenChunkTokens * topK * interSize]" },
{ "id": "slotList", "dtype": "uint32", "shape": "[max(1, groupSlots)]" },
{ "id": "tileMeta", "dtype": "uint32", "shape": "[1 + 3 * groupMaxTiles]" },
{ "id": "slotOut", "dtype": "float32", "shape": "[max(1, hiddenChunkTokens * topK * hiddenSize)]" }
],
"passes": [
{
"id": "route_stage",
"name": "QMoE.RouteStage",
"shader": "qmoe-route-stage.wgsl.jinja",
"bindings": "route",
"dispatch": { "threads": "numTokens", "workgroupSize": "constants.workgroupSize" }
},
{
"id": "token_chunks",
"repeat": { "count": "hiddenChunkCount", "index": "chunk" },
"passes": [
{
"id": "group_stage",
"name": "QMoE.GroupStage",
"shader": "expert-group-slots.wgsl.jinja",
"bindings": "group",
"dispatch": {
"threads": "constants.groupRouteWorkgroup",
"workgroupSize": "constants.groupRouteWorkgroup"
}
},
{
"id": "fc1_activation_stage",
"name": "QMoE.FC1ActivationStageGrouped",
"shader": "qmoe-fc1-activation-grouped.wgsl.jinja",
"bindings": "fc1Grouped",
"dispatch": { "x": "groupMaxTiles", "y": "ceilDiv(interSize, groupTileN)" }
},
{
"id": "output_stage",
"name": "QMoE.OutputStageGrouped",
"shader": "qmoe-output-grouped.wgsl.jinja",
"bindings": "outputGrouped",
"dispatch": { "x": "groupMaxTiles", "y": "ceilDiv(hiddenSize, groupTileN)" }
},
{
"id": "mix_stage",
"name": "QMoE.MixStage",
"shader": "qmoe-mix-stage.wgsl.jinja",
"bindings": "mix",
"dispatch": {
"threads": "min(hiddenChunkTokens, numTokens - repeat.chunk * hiddenChunkTokens) * hiddenSize",
"workgroupSize": "constants.workgroupSize"
}
}
]
}
]
},
{
"id": "quant_gemv_routed",
"priority": 20,
"when": ["decodeContract"],
"constants": { "decodeLanes": "tunables.decodeLanes", "decodeRows": "decodeRows" },
"intermediates": [
{ "id": "routeExpert", "dtype": "uint32", "shape": "[numTokens * topK]" },
{ "id": "routeMix", "dtype": "float32", "shape": "[numTokens * topK]" },
{ "id": "hiddenAct", "dtype": "float32", "shape": "[hiddenChunkTokens * topK * interSize]" }
],
"passes": [
{
"id": "route_stage",
"name": "QMoE.RouteStage",
"shader": "qmoe-route-stage.wgsl.jinja",
"bindings": "route",
"dispatch": { "threads": "numTokens", "workgroupSize": "constants.workgroupSize" }
},
{
"id": "token_chunks",
"repeat": { "count": "hiddenChunkCount", "index": "chunk" },
"passes": [
{
"id": "fc1_activation_stage",
"name": "QMoE.FC1ActivationStageGemv",
"shader": "qmoe-fc1-activation-gemv.wgsl.jinja",
"bindings": "fc1ActivationScheduled",
"dispatch": {
"x": "ceilDiv(interSize, decodeRows)",
"y": "min(hiddenChunkTokens, numTokens - repeat.chunk * hiddenChunkTokens) * topK"
}
},
{
"id": "output_stage",
"name": "QMoE.OutputStageGemv",
"shader": "qmoe-output-gemv.wgsl.jinja",
"bindings": "outputScheduled",
"dispatch": {
"x": "ceilDiv(hiddenSize, decodeRows)",
"y": "min(hiddenChunkTokens, numTokens - repeat.chunk * hiddenChunkTokens)"
}
}
]
}
]
},
{
"id": "quant_split_routed",
"priority": 10,
"when": ["quantContract", "workgroupSizeOk", "hiddenChunkFits", "routedScratchFits", "interSize > 0"],
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{ "id": "routeExpert", "dtype": "uint32", "shape": "[numTokens * topK]" },
{ "id": "routeMix", "dtype": "float32", "shape": "[numTokens * topK]" },
{ "id": "hiddenAct", "dtype": "float32", "shape": "[hiddenChunkTokens * topK * interSize]" }
],
"passes": [
{
"id": "route_stage",
"name": "QMoE.RouteStage",
"shader": "qmoe-route-stage.wgsl.jinja",
"bindings": "route",
"dispatch": { "threads": "numTokens", "workgroupSize": "constants.workgroupSize" }
},
{
"id": "token_chunks",
"repeat": { "count": "hiddenChunkCount", "index": "chunk" },
"passes": [
{
"id": "fc1_activation_stage",
"name": "QMoE.FC1ActivationStage",
"shader": "qmoe-fc1-activation-stage.wgsl.jinja",
"bindings": "fc1Activation",
"dispatch": {
"threads": "min(hiddenChunkTokens, numTokens - repeat.chunk * hiddenChunkTokens) * topK * interSize",
"workgroupSize": "constants.workgroupSize"
}
},
{
"id": "output_stage",
"name": "QMoE.OutputStage",
"shader": "qmoe-output-stage.wgsl.jinja",
"bindings": "output",
"dispatch": {
"threads": "min(hiddenChunkTokens, numTokens - repeat.chunk * hiddenChunkTokens) * hiddenSize",
"workgroupSize": "constants.workgroupSize"
}
}
]
}
]
}
]
}
|