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benchmark.md 8.82 KB
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Caize Wu 提交于 2023-04-13 21:58 . Update benchmark.md

Benchmark

Test Models

mnist

mnist: 28x28x1 input,4->8->16, pad valid
mnist_q_valid.h 2.4KB Flash 1.4KB RAM
suit for MCU have >=16KB Flash, >=2KB RAM

cifar

cifar: 32x32x3 input, 32->32->64->1024->10, 5x5 conv
cifar10_q.h 89KB Flash 11KB RAM
suit for MCU have >=128KB Flash, >=20KB RAM

vww96

vww96: vww model based on mobile net v1 0.25 96x96x3 input
vww96_q.tmdl 227KB Flash 54KB RAM
suit for MCU have >=256KB Flash, >=64KB RAM
https://mlcommons.org/en/inference-tiny-07/

mbnet128

mbnet128: mobile net v1 0.25 128x128x3 input
mbnet128_0.25_q.tmdl 485KB Flash 96KB RAM
suit for MCU have >=512KB Flash, >=128KB RAM
https://github.com/fchollet/deep-learning-models/releases

Test Record

model infer time unit is ms;
Sort by performance, compare priority: mbnet128 > vww96 > cifar > mnist

Note1: arduino run another smaller mnist model due to limited memory
Note2: all model record fastest model type's infer time, for example, C906 use FP16 result. Note3: XXX means impossible run this model on that chip

Chip/Board Core Flash RAM Freq mbnet vww96 cifar mnist Note
BL808's NPU BLAI 16MB 0.8+64MB 320M 5 3 <1 <1
i5-4590T AMD64 256GB 8GB 2000M 7/24 5/17 0.9/4 0.04/<1 native/wasm
RK3399's A72 ARM A72 32GB 4GB 1800M 15 10 3 0.07
TH1520 RV64V(C910) 16GB 4GB 1848M 17 10.4 3.6 0.15 fp16
RK3399's A53 ARM A53 32GB 4GB 1600M 29 19 5 0.14
D1-H RV64V 128GB 2GB 1008M 43 22 3.5 0.29
SSD201 ARM A7 128MB 64MB 1200M 66 42 10 0.23
ZYNQ7010's A9 ARM A9 32GB 1GB 667M 66 44 7.8 0.34
BL808's C906 RV64V 16MB 0.8+64MB 480M 81 57 10 <1
STM32H750 ARM CM7 1MB 1024KB 480M 94 64 15 <1
V851S' E907 RV32P 128MB 4MB 600M 108 99 32 0.5
HPM6750 Andes D45RV32IMAFDCP 8MB 2MB+32MB 816M 174 112 33 0.45
BL808's E907 RV32P 16MB 0.8+64MB 320M 188 149 35 <1 mdl in psram
F1C200S ARM926EJ-S 16MB 64MB 608M 213 145 38.5 0.75
MT7621A MIPS1004Kc 128MB 128MB 880M 413 244 41 1 need confirm
AT32F403A ARM CM4 1MB 96KB 240M 477 136 30 0.6 mbnet in 224k ram mode
STM32G474RE ARM CM4 512KB 128KB 170M XXX 195 43 1
CH32V307 RV32FQingKe V4F 480KB 128KB 144M XXX 357 64 1
STM32F411CE ARM CM4 512KB 128KB 150M 558 366 75 2
W801 CSKYV2 ck804ef 2MB 160+128KB+8MB 240M 606 364 52 <2 mdl in psram/(or sram if fit)
ESP32-S3 Xtensa LX7 8MB 512KB 240M 610 381 86 5 mdl in flash
LPC4337 ARM CM4F 1MB 136KB 204M 654 627 91 3 need confirm
XR806 ARMv8-MStar-MC1 2MB 288KB 160M 712 453 104 1
ESP32 Xtensa LX6 4MB 520KB 240M 755 476 132 2 mdl in flash
ACM32F403 ARM CM33 512KB 192KB 180M XXX 458 139 2
STM32F767 ARM CM7 2MB 512KB 216M 869 640 185 3 need confirm
SC5864B's DSP HIFI3 32MB 8MB+192KB 160M 805 --- --- 15 need confirm
STM32L496 ARM CM4 1MB 320KB 80M 809 695 162 3
BK7256 RISC-V 4MB 512KB 320M 1036 678 186 2.8
NRF52832 ARM CM4 512KB 64KB 64M XXX xxx 217 4
ESP32-S2 Xtensa LX7 4MB 320KB 240M 1079 659 241 2.5 need confirm
RP2040 ARM CM0+ 16MB 264KB 280M 1211 716 200 2 overclock 280M
CH32V203G6 RV32QingKe V4B 32KB 10KB 144M XXX XXX XXX 2.5
ESP32-C3 RV32 4MB 400KB 160M 2370 1430 127 6 mdl in flash
MM32F3270 ARM CM3 512KB 128KB 96M 3126 2919 257 11
Nuclei N300 RV32IMAFDC 16MB 512KB 16M XXXX 2946 795 11 need confirm
STM32F103RC ARM CM3 256KB 48KB 72M XXX XXX 445 7
STM32F103C8 ARM CM3 64KB 20KB 72M XXX XXX XXX 7
RiscyD2 RV32IM 48KB 8KB 100M XXX XXX XXX 12 Digilent Arty A7-35T
CH32V103 RV32QingKe V3A 64KB 20KB 72M XXX XXX XXX 13
SAMD21G18 ARM CM0+ 256KB 32KB 48M XXX XXX 700 14 seeed XIAO
APM32F072CB ARM CM0+ 128KB 16KB 48M XXX XXX XXX 17
STM32G030F6 ARM CM0+ 32KB 8KB 64M XXX XXX XXX 18
CM0(Kintex-7) ARM CM0 --- 1024KB 50M XXX XXX 1362 23 Kintex-7
CH582 RV32QingKe V4A 448KB 32KB 60M XXX XXX XXX 31
STC32G12K128 80251 128KB 12KB 35M XXX XXX XXX 37
PicoRV32(GW2A) RV32 1MB 64KB 54M XXX XXX 26935 385 Tang Primer 20K
Atmega328 AVR 32KB 2KB 16M XXX XXX XXX 50(*)

Normalization to 100M freq to compare CPU efficiency, using cifar model:

Chip/Board Core cifar(ms)
BL808's NPU BLAI 2
D1-H RV64V 35
BL808's C906 RV64V 48
RK3399's A72 ARM A72 52
ZYNQ7010's A9 ARM A9 52
TH1520 RV64V(C910) 66
STM32H750 ARM CM7 72
AT32F403A ARM CM4 72
STM32G474RE ARM CM4 73
RK3399's A53 ARM A53 79
CH32V307 RV32 IMAC 92
BL808's E907 RV32P 112
STM32F411CE ARM CM4 113
SSD201 ARM A7 123
W801 CSKYV2 ck804ef 125
Nuclei N300 RV32IMAFDC 127
STM32L496 ARM CM4 130
NRF52832 ARM CM4 139
XR806 ARMv8-MStar-MC1 166
ESP32-C3 RV32 203
ESP32-S3 Xtensa LX7 206
F1C200S ARM926EJ-S 234
MM32F3270 ARM CM3 247
ACM32F403 ARM CM33 250
ESP32 Xtensa LX6 317
STM32F103RC ARM cM3 320
SAMD21G18 ARM CM0+ 336
MT7621A MIPS1004Kc 360
RP2040 ARM CM0+ 560
ESP32-S2 Xtensa LX7 578
CM0(Kintex-7) ARM CM0 681
PicoRV32(GW2A) RV32 14545

Infer Time & Input Size

mbnet infer time under different input size
BL808 C906 core 480M, use RV64V, FP16 model

input size infer time
96x 96 60ms
128x128 81ms
160x160 156ms
192x192 183ms
224x224 296ms

Optimization

TM_FASTSCALE

Optimization for MCU which don't have FPU
STM32F103C8 run mnist

Options infer time
TM_FASTSCALE=0 16ms
TM_FASTSCALE=1 10ms

TM_ARCH_ARM_SIMD

Optimization for ARM MCU which have DSP (Cortex-M4,M7,etc.), suoport INT8 acceleration
STM32F411CE run mbnet 0.25, 128x128x3 input

Options infer time
TM_ARCH_OPT0 && INT8 1199ms
TM_ARCH_ARM_SIMD && INT8 840ms

TM_ARCH_ARM_MVEI

Optimization for ARM MCU which have MVEI instructions (Cortex-M55,etc.), suoport INT8 acceleration.

Experimental, not test data.

TM_ARCH_ARM_NEON

Optimization for ARM MPU which have NEON instructions (Cortex-A7 and newer), suoport INT8/FP32 acceleration

Raspberry Pi4 single core run mbnet 1.0, 224x224x3 input
(NEON INT8 not well optimized)

ARCH MDL_TYPE OPT0 time OPT1 time
TM_ARCH_CPU INT8 860ms 821ms
TM_ARCH_CPU FP32 2307ms 2271ms
TM_ARCH_ARM_NEON FP32 1275ms 1223ms
TM_ARCH_ARM_NEON INT8 959ms 923ms

TM_ARCH_RV32P

Optimization for RISC-V MCU which have P-extend instructions (like T-Head E907), suoport INT8 acceleration
BL808 E907 core run mbnet 0.25, 128x128x3 input (mdl in psram, cpu run in 320M, O2)

ARCH MDL_TYPE OPT0 time OPT1 time
TM_ARCH_CPU INT8 443ms 283ms
TM_ARCH_RV32P INT8 345ms 188ms

TM_ARCH_RV64V

Optimization for RISC-V MCU which have V-extend instructions (like T-Head C906), suoport INT8/FP32 acceleration
BL808 C906 core run mbnet 0.25, 128x128x3 input (mdl in psram, VLEN=128, cpu run in 480M, O2)

ARCH MDL_TYPE OPT0 time OPT1 time
TM_ARCH_CPU INT8 153ms 125ms
TM_ARCH_CPU FP32 215ms 177ms
TM_ARCH_RV64V INT8 123ms 95ms
TM_ARCH_RV64V FP32 160ms 121ms
TM_ARCH_RV64V FP16 129ms 81ms

TM_ARCH_CSKYV2

Optimization for CskyV2 MCU which have DSP instructions (like ck804ef), suoport INT8 acceleration
w801 ck804ef core run mbnet 0.25, 128x128x3 input (mdl in psram, cpu run at 240M,psram overclock to 120M, O3, with data cache on)

ARCH MDL_TYPE OPT0 time OPT1 time
TM_ARCH_CPU INT8 950ms 816ms
TM_ARCH_CSKYV2 INT8 724ms 606ms

Compare to other infer library

Use SmallCifar model. TinyMaix use stride=2's time multipy by 4.
NNoM&TinyMaix run with STM32H750@218M, other run with STM32F746@216M

InferLib time(ms)
TFlite-micro 393
MicroTVM untuned 294
TinyMaix CPU O0 224
TinyMaix CPU O1 204
TinyMaix SIMD O0 176
NNoM 159
MicroTVM tuned 157
CMSIS-NN 136
TinyMaix SIMD O1 132
tinyengine 129
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