NKIBench / summary.json
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{
"swiglu": {
"seed": "./seeds/swiglu.yaml",
"cases": {
"2": {
"values": {
"K": 1024,
"M": 4096,
"N": 3072
},
"impls": [
{
"task": "./reference/swiglu_M4096_N3072_K1024_numpy_2.py",
"kernel": "./kernels/swiglu_M4096_N3072_K1024_0.py"
}
]
}
}
},
"matmul_add_rmsnorm": {
"seed": "./seeds/matmul_add_rmsnorm.yaml",
"cases": {
"1": {
"values": {
"K": 2048,
"M": 4096,
"N": 2048
},
"impls": [
{
"task": "./reference/matmul_add_rmsnorm_M4096_N2048_K2048_numpy_1.py",
"kernel": "./kernels/matmul_add_rmsnorm_M4096_N2048_K2048_0.py"
}
]
}
}
},
"add_rmsnorm_matmul": {
"seed": "./seeds/add_rmsnorm_matmul.yaml",
"cases": {
"2": {
"values": {
"K": 1024,
"M": 4096,
"N": 2048
},
"impls": [
{
"task": "./reference/add_rmsnorm_matmul_M4096_N2048_K1024_numpy_1.py",
"kernel": "./kernels/add_rmsnorm_matmul_M4096_N2048_K1024_0.py"
}
]
}
}
},
"matmul": {
"seed": "./seeds/matmul.yaml",
"cases": {
"3": {
"values": {
"K": 5120,
"M": 4096,
"N": 12288
},
"impls": [
{
"task": "./reference/matmul_M4096_N12288_K5120_numpy_2.py",
"kernel": "./kernels/matmul_M4096_N12288_K5120_0.py"
}
]
}
}
},
"gqa_full": {
"seed": "./seeds/gqa_full.yaml",
"cases": {
"0": {
"values": {
"B": 1,
"D": 128,
"KH": 8,
"N": 4096,
"QH": 16
},
"impls": [
{
"task": "./reference/gqa_full_B1_N4096_QH16_KH8_D128_numpy_2.py",
"kernel": "./kernels/gqa_full_B1_N4096_QH16_KH8_D128_0.py"
}
]
}
}
},
"rmsnorm_matmul": {
"seed": "./seeds/rmsnorm_matmul.yaml",
"cases": {
"2": {
"values": {
"K": 1024,
"M": 4096,
"N": 2048
},
"impls": [
{
"task": "./reference/rmsnorm_matmul_M4096_N2048_K1024_numpy_1.py",
"kernel": "./kernels/rmsnorm_matmul_M4096_N2048_K1024_0.py"
}
]
}
}
},
"rope_single_freq_apply": {
"seed": "./seeds/rope_single_freq_apply.yaml",
"cases": {
"1": {
"values": {
"B": 1,
"H": 64,
"N": 4096,
"D": 128
},
"impls": [
{
"task": "./reference/rope_single_freq_apply_B1_H64_N4096_D128_numpy_1.py",
"kernel": "./kernels/rope_single_freq_apply_B1_H64_N4096_D128_0.py"
}
]
}
}
},
"bmm": {
"seed": "./seeds/bmm.yaml",
"cases": {
"2": {
"values": {
"B": 16,
"K": 64,
"M": 4096,
"N": 4096
},
"impls": [
{
"task": "./reference/bmm_B16_M4096_K64_N4096_numpy_1.py",
"kernel": "./kernels/bmm_B16_M4096_K64_N4096_0.py"
}
]
}
}
},
"bmm_softmax": {
"seed": "./seeds/bmm_softmax.yaml",
"cases": {
"2": {
"values": {
"B": 16,
"K": 64,
"M": 4096,
"N": 4096
},
"impls": [
{
"task": "./reference/bmm_softmax_B16_K64_M4096_N4096_numpy_1.py",
"kernel": "./kernels/bmm_softmax_B16_K64_M4096_N4096_0.py"
}
]
}
}
},
"transpose_matmul": {
"seed": "./seeds/transpose_matmul.yaml",
"cases": {
"2": {
"values": {
"K": 2048,
"M": 4096,
"N": 10944
},
"impls": [
{
"task": "./reference/transpose_matmul_M4096_K2048_N10944_numpy_1.py",
"kernel": "./kernels/transpose_matmul_M4096_K2048_N10944_0.py"
}
]
}
}
},
"lora": {
"seed": "./seeds/lora.yaml",
"cases": {
"2": {
"values": {
"K": 5120,
"M": 4096,
"N": 12288,
"R": 128
},
"impls": [
{
"task": "./reference/lora_M4096_N12288_K5120_R128_numpy_1.py",
"kernel": "./kernels/lora_M4096_N12288_K5120_R128_0.py"
}
]
}
}
},
"adamw": {
"seed": "./seeds/adamw.yaml",
"cases": {
"2": {
"values": {
"M": 10944,
"N": 2048
},
"impls": [
{
"task": "./reference/adamw_M10944_N2048_numpy_1.py",
"kernel": "./kernels/adamw_M10944_N2048_0.py"
}
]
}
}
},
"silu": {
"seed": "./seeds/silu.yaml",
"cases": {
"2": {
"values": {
"M": 4096,
"N": 7168
},
"impls": [
{
"task": "./reference/silu_M4096_N7168_numpy_0.py",
"kernel": "./kernels/silu_M4096_N7168_0.py"
}
]
}
}
},
"mamba": {
"seed": "./seeds/mamba.yaml",
"cases": {
"2": {
"values": {
"C": 256,
"M": 7168,
"S": 16
},
"impls": [
{
"task": "./reference/mamba_M7168_C256_S16_numpy_1.py",
"kernel": "./kernels/mamba_M7168_C256_S16_0.py"
}
]
}
}
}
}