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Highly Optimized Low Precision Kernels

Our kernels are based on x64 template library jblas.

Support Matrix

Limited by the graph framework, we only add kernels which accept float tensor as input and output tensor.

input dtype output dtype compute type compute ISA
float32 float32 float32 AVX2
float32 float32 float32 AVX512F
float321 float322 int8 AVX512_VNNI
float321 float322 int8 AVX_VNNI
float321 float322 int8 AMX_INT8
float32/bf16 float32/bf16 bf16 AMX_BF16
float32/fp16 float32/fp16 fp16 AVX512_FP16

1: per-batch and per-K group-wise dynamic quantization for input tensor, where per-K group-wise also applies to weight quantization group size of weight tensor; support both symmetric and asymmetric quantization. 2: per-batch dynamic dequantization for output tensor.

Weight-only Quantization Support

dtype algo group size
int4 symmetric int8 truncated quant2 multiplier of 8, -11
int4 symmetric int4 full range3 multiplier of 8, -11
int4 asymmetric int4 full range3 multiplier of 8, -11
int8 symmetric multiplier of 8, -11
fp4 multiplier of 8
nf4 multiplier of 8

1: group size=-1 means per channel quantization on output channel (or group size equals to input channel size). 2: truncated quant means keep the high 4 bits of int8 quantization result for model saving and computation. 3: full range is a quantization method that utilizes the -8 value of int4 range compared with the normal int4 range [-7,7].

NOTE: AMX_INT8 requires group size is aligend to 128 (best hardware efficiency)

Fusion Support

We support three kinds of kernel fusion for transformer models: QKV, MHA (multi-head attention), and FFN (feed-forward network) fusion.

fusion type models runtime ISA
QKV GPT-J
LLaMA
AMX_INT8, AVX512_VNNI, AVX_VNNI
FFN GPT-J
LLaMA
BLOOM
ChatGLM
Falcon
MPT
AMX_INT8, AVX512_VNNI, AVX512F, AMX_BF16, AVX_VNNI, AVX2
MHA

Referring the fused-attention doc for details

Fastest Configuration for CPUs

codename weight config runtime ISA
Sapphire Rapids any int4
group size=-1
compute type=int8
AMX_INT8
Ice Lake
Cascade Lake
Cooper Lake
Tiger Lake
Rocket Lake
any int4
group size=-1
compute type=int8
AVX512_VNNI
Skylake any 4bits
group size=-1
compute type=fp32
AVX512F
Alder Lake (12th Gen)
Raptor Lake (13th and 14th Gen)
any 4bits
group size=-1
compute type=int8
AVX_VNNI
Older architecture (before 12th Gen) any 4bits
group size=-1
compute type=fp32
AVX2