f6f734f44d
vulkan int8 kernels ( #6751 )
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* vulkan: add int8 kernels for core layers
Implement Vulkan int8 paths for convolution, convolutiondepthwise, innerproduct, and gemm with scalar fallback and integer dot product shader branches. Add goal.md and enable existing int8 unit tests for Vulkan coverage.
* enable int8 gpu benchmark
2026-06-17 17:39:49 +08:00
6b4f6f95e5
[feat](benchmark): replace load_param with load_param_mem ( #6286 )
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* [feat](benchmark): replace load_param with load_param_mem
* [docs](benchmark): update benchmark docs
* refactor(benchmark): remove model registry and optimize param loading
* fix(benchmark): correct README param description
* refactor(benchmark): rename header file
* update doc
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Co-authored-by: nihui <nihuini@tencent.com >
Co-authored-by: nihui <shuizhuyuanluo@126.com >
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com >
2026-01-08 14:23:00 +08:00
b8a1c92cce
fix format specifier for size_t to support 64-bit values ( #6315 )
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---------
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com >
2025-09-12 14:00:27 +08:00
b5bc05e2e8
drop vulkan shader pack8 ( #6270 )
2025-08-22 11:05:59 +08:00
4d8220ce22
Skip int8 model on GPU and merge from upstream ( #6174 )
2025-07-12 17:06:46 +08:00
171b9d1bba
use spdx license header, copyright Tencent ( #6152 )
2025-07-08 11:01:29 +08:00
24a3b99f1f
drop layer support_image_storage and option use_image_storage ( #6126 )
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* fix pyncnn build
2025-06-16 11:23:41 +08:00
ded0b78bb2
fix nvidia vulkan crash on exit ( #5234 )
2023-12-20 11:32:53 +08:00
465debe9bb
Add print statements for 4 dimensions benchmark ( #5148 )
2023-11-15 11:43:59 +08:00
a1e3ebf8e5
implement simplemath ( #4905 )
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* complete abs, fmod and sin function in simplemath.h
* remove some unused variables in simplemath.cpp
* modify test-coverage.yml and add some functions to simplemath.cpp
* modify erf.cpp which included math.h
* include platform.h for NCNN_SIMPLEMATH definition
* move utility constants and functions in simplemath.h to simplemath.cpp
* guard simplemath functions with extern "C"
* add NCNN_EXPORT macro in simplemath.h
* include plateform.h and guard all declarations with NCNN_SIMPLEMATH
* clean unused code in test_unaryop.cpp
* guard #include <vector> with NCNN_SIMPLEMATH in benchncnn.cpp
* add 'static' to guard functions that not declarated in header file
* modify sin and cos with better implementation
---------
Co-authored-by: HonestDeng <HonestDeng@users.noreply.github.com >
2023-10-23 10:51:51 +08:00
a24787b32b
feat(benchmark/benchncnn.cpp): support user defined case ( #4782 )
2023-08-11 11:17:24 +08:00
0e09ae1290
Reimplement the sleep() and get_current_time() functions using modern C++. ( #4677 )
2023-05-16 14:22:29 +08:00
544adbb051
Fix destory in gpu ( #4653 )
2023-04-20 13:51:00 +08:00
e36dbdfd93
Fix core dump in benchmark ( #4648 )
2023-04-19 22:49:37 +08:00
804ac3421d
infrastructure and optimization for a53 and a55 ( #4596 )
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* new api for detecting arm midr and a53 a55 arch info wrapper
* let a35 be a53 :P
* a53 bf16s
* detect running core
2023-04-07 12:47:05 +08:00
b853b3d132
get_physical_cpu_count api family ( #4302 )
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* get_physical_cpu_count api family
* set default to physical big cpu
* always treat smt core as big core
* is_smt_cpu
* get max freq mhz on windows
* windows thread affinity
2022-10-31 10:48:22 +08:00
9426e21166
Memory Pool Improvement For Variadic Sized Inputs ( #4190 )
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* Simple miss count for better space efficiency
* Simple double ended greedy;
* Add size drop threshold setter;
* set workspace allocator cr to zero as we had some sort of recylcing capability :P
Co-authored-by: LinHeLurking <LinHeLurking@users.noreply.github.com >
Co-authored-by: nihuini <nihuini@tencent.com >
2022-10-09 10:42:51 +08:00
1d0917c83b
fix build with very old gcc ( #4048 )
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* clear bom marker, avoid vector data function
2022-07-20 14:46:51 +08:00
962a49069a
add the param file of fastestdet in benchmark ( #4026 )
2022-07-12 21:55:03 +08:00
6fd801b6d7
feat(src/layer): add vision_transformer benchmark ( #3730 )
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* feat(src/layer): add vision_transformer benchmark and relative layer
* refactor(testutil.h): add para for RandomMat
2022-05-17 16:13:49 +08:00
009d607a15
add the param file of yolo-fastest in benchmark ( #3470 )
2022-01-01 22:39:57 +08:00
2112a4d7c3
add the param file of nanodet_m in benchmark ( #3047 )
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* add the param file of nanodet_m in benchmark
* add Noop layer into nanodet_m param for benchmark
* update nanodet_m.param
2021-07-03 14:46:51 +08:00
26dc9820e4
custom mlir ncnn optimize pass, add efficientnetv2_b0 benchmark
2021-05-19 16:34:18 +08:00
8cc8cd716a
Add get input and output names ( #2890 )
2021-05-17 19:11:37 +08:00
e4a4b51d27
openmp on webassembly ( #2234 )
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* openmp on webasm works
* fix compile flags
* dynamic kmp runtime initialization
* clang simpleomp ci
* fix dispatch on unique cpu
2020-10-20 14:41:03 +08:00
8b0c46c45d
A single approach was used to suppress the msvc C4996 compiler warning [_CRT_SECURE_NO_WARNINGS] ( #2208 )
2020-10-13 21:20:05 +08:00
1d1cb29869
Fixed compile warning due to default cast ( #2201 )
2020-10-13 16:23:12 +08:00
11cffce114
armv8.2 infrastructure ( #1856 )
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* runtime cpu dispatch
* force thread one
* disable openmp for coverage
* simplify test layer
* print NCNN_TARGET_ARCH
* less ci build variants
* weight fp16 storage option
* test convdw int8
* apple a12 a13
* ncnn_add_layer ncnn_add_shader cmake macro
2020-07-19 19:29:52 +08:00
fe6bc1ed4d
Ci rv64gcv and rv64gc ( #1936 )
2020-07-14 22:55:19 +08:00
cdbff653b8
Add yolov4 example option. ( #1913 )
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* Add yolov4 example option.
Add yolov4-tiny for benchmark.
* Restyled by astyle
* Restyled by clang-format
* Restyled by astyle
Co-authored-by: Restyled.io <commits@restyled.io >
2020-07-05 21:44:41 +08:00
164273de61
online pipeline cache ( #1792 )
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* online pipeline cache wip
* device-wide pipeline cache
* enable model-wide pipeline cache
* drop pre-created shader modules
* always use pipeline cache
* use implicit model-wide pipeline cache, code format
* code clean
2020-07-04 12:30:50 +08:00
9bb06e46cf
implicit gpu instance creation, fix #1849
2020-06-18 19:02:01 +08:00
3ef995ed1e
format code style and setup restyled.io ( #1840 )
2020-06-13 22:17:51 +08:00
da09e5e7f1
Adding channel padding support for blazeface model. ( #1826 )
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* Add channel padding and blazeface model support.
* remove python binding
* remove std::min usage
* fix reference blob usage
* Increased padding test coverage
* implement requested changes
2020-06-09 19:25:40 +08:00
03a5378651
efficientnet-b0 and regnety-400m benchmark
2020-06-03 14:00:14 +08:00
054ec09195
adreno device blacklist
2020-06-01 16:16:53 +08:00
d232272db0
lower end gpu friendly
2020-05-19 16:07:34 +08:00
b71f22d074
report adreno info, benchncnn enable image storage on adreno
2020-05-19 12:35:52 +08:00
9a9a618229
image storage is mandatory, less options makes life easier
2020-05-08 00:09:35 +08:00
62da1228e1
adreno image shader + fp16 + fp16a ( #1714 )
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* wip
* wip
* fix
* image and imageview can not be destroyed until command execution ends
* fast copy path for tightly packed data
* wip
* texture load works
* 1d 3d image
* record clone image, multiple commands share one image reference
* upload download image
* layer forward accept vkimagemat
* vkimagemat graph works
* staging vkimagemat for passing dynamic parameters, macro for fp32+image shader, padding image shader
* vkimagemat elemsize
* convolution test pass
* conv1x1s1 image shader
* fast staging image allocator from host memory, pooling image shader
* convolutiondepthwise image shader
* innerproduct image shader
* packing image shader
* crop deconvolution image shader
* resolve spirv binding types
* image fp16 and fp16a, cast image shader
* eltwise image shader
* wip
* absval image shader
* deconvolutiondepthwise image shader
* concat image shader, squeezenet works
* noop split image shader
* uniform precision hint
* layer support_image_storage
* wip
* vulkan device utility operator
* command is storage and packing option aware
* fallback to cpu on image allocation failed, mobilenetssd works
* flatten image shader, enable more test
* ci test
* check imgfp32 imgfp16 imgfp16a features
* fix ci test
* fix ci test
* upgrade swiftshader
* wip
* opt aggressive
* imgfp16p
* opt none
* convolution winograd image shader
* fix flush range, fast copy path for continous buffer
* minor fix
* fix innerproduct
* wip ...
* wip
* cast fix
* packing test
* wip
* image fp16p is fp16p
* wip
* silence
* more line info
* code clean
* softmax image shader
2020-04-30 17:08:30 +08:00
06e129d259
add skip cooling down option ( #1566 )
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* add option for cooling down
* add option for cooling down
add the option usage
add benchmark of RTX2080
* add benchmark of rtx2060
2020-02-29 19:27:06 +08:00
6f2ef1932d
int8 code refactoring wip, add int8 test
2020-01-05 00:08:11 +08:00
447b1369f5
Fix warnings on Visual Studio ( #1422 )
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* Change DataReader::read()'s signature to fix warning C4267
This CL fixes lots of warning "C4267: 'initializing': conversion from
'size_t' to 'int'" in our codebase by matching DataReader::read()'s
signature to fread().
* Fix warnings C4244 and C4267 in tools/ncnnoptimize.cpp
C4244: 'initializing': conversion from 'double' to 'float',
possible loss of data
C4267: 'initializing': conversion from 'size_t' to 'int',
possible loss of data
* Fix warning C4244 in src\layer\selu.cpp
C4244: '=': conversion from 'double' to 'float', possible loss of data
* Fix warning C4244 in src\layer\cast.cpp
C4244: '=': conversion from 'double' to 'float', possible loss of data
C4244: 'return': conversion from 'float' to 'signed char', possible loss of data
* Fix warning C4244 in src\layer\psroipooling.cpp
C4244: 'initializing': conversion from 'double' to 'float',
possible loss of data
C4244: 'initializing': conversion from 'double' to 'int',
possible loss of data
2019-12-13 16:19:13 +08:00
2e59da35a9
fill input and weight data with zero
2019-10-28 19:43:44 +08:00
02b07b3e43
update qcom810 and iphone5s benchmark
2019-10-28 15:22:05 +08:00
64333429bb
data reader wrapper, fix #1325
2019-10-25 19:18:40 +08:00
567e2bd501
a dirty hack for resolving int8 pack4 crash
2019-10-25 11:48:39 +08:00
f8caef7691
add shufflenet_v2 benchmark
2019-10-24 16:53:47 +08:00
9d4255a4a4
add mobilenet_v3 benchmark
2019-08-19 19:55:31 +08:00
f5eee84185
Update mobilenetv2-yolov3 ( #1165 )
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* Add mobilenetv2_yolov3 ,and remove old model
* Recovery yolov2
* Update link
2019-08-02 16:42:16 +08:00
nihui