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Benchmark for XuanTie CPU

Welcome to the XuanTie AI Benchmark Suite! This repository contains a comprehensive collection of benchmark tests specifically designed for RISC-V CPUs with RVV/RVM. Our goal is to provide developers, researchers, and enthusiasts with a suite of tools to evaluate the performance and efficiency of AI algorithms running on RISC-V architecture.

Features

Model Original Model License quantization c907 c908
bert url Apache-2.0 license float32 url url
float16 url url
int8_asym_w_sym url url
float16_w_int8 url
efficientnet url Apache-2.0 license float32 url url
float16 url url
int8_asym_w_sym url url
float16_w_int8 url
mobilenetv2 url Apache-2.0 license float32 url url
float16 url url
int8_asym_w_sym url url
float16_w_int8 url
mobileVit url apple float32 url url
float16 url url
int8_asym_w_sym url url
float16_w_int8 url
resnet50 url Apache-2.0 license float32 url url
float16 url url
int8_asym_w_sym url url
float16_w_int8 url
retinaface url MIT float32 url url
float16 url url
int8_asym_w_sym url url
float16_w_int8 url
shufflenetv2 url Apache-2.0 license float32 url url
float16 url url
int8_asym_w_sym
float16_w_int8
swin url MIT float32 url url
float16 url url
int8_asym_w_sym url url
float16_w_int8 url
yolov5n url AGPL-3.0 float32
float16
int8_asym_w_sym
float16_w_int8

Getting Started

Requirements

Clone codes

# 1. download codes
git clone repo_url
# 2. prepare submodules
cd REPO_DIR
git submodule init
git submodule update

Evaluations

Take c908/float16/onnx_mobilenetv2-12 as an example

cd c908/float16/onnx_mobilenetv2-12
make -f makefile.c908 hhb_runtime

# download binary file for model(click the url in the above table or wget)
wget http://yocbook.oss-cn-hangzhou.aliyuncs.com/linux_image/XuanTie_V1.0.5/xtai-benchmark-bm/908_float16_onnx_mobilenetv2-12_hhb.bm.tar.gz
tar -zxvf 908_float16_onnx_mobilenetv2-12_hhb.bm.tar.gz
mv 908_float16_onnx_mobilenetv2-12_hhb.bm hhb.bm

# run with qemu
make -f makefile.c908 run_sim