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58d3b77970
- Using float instead of double for floating point matrix multiplications (in core/src/matmul.simd.hpp) reduces a lot the computation time
58 lines
1.4 KiB
Markdown
58 lines
1.4 KiB
Markdown
# Optimization
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This doc details some optimizations done for OpenCV to run faster on the ESP32.
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Activating optimization
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----------------------------
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To activate the optimization for the ESP32, the CMake parameter `-DESP32_OPTIMIZATION=ON` must be enabled. Every optimization done will be disabled if this parameter is OFF.
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## Floating point support
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The ESP32 only have a single precision Floating Point Unit (no double precision). Therefore, OpenCV functions using double types are very slow.
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### Matrix multiplications
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In files `core/matmul.dispatch.cp` and `core/matmul.simd.hpp`.
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Results by multiplying 100x6 * 6x100 matrices:
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1. Initial test : 60 ms
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2. Changing `alpha` and `beta` from double to float in `GEMMsingleMult()` function: 12ms
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3. Changing `alpha` and `beta` from double to float in `gemmImpl()` function: 4.6ms
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Results by multiplying 150x100 * 100x150 matrices:
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1. Initial test: 2757ms
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2. Changing double in `GEMMStore()` function: 888ms
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## Esp-dsp library
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The ESP32 processor has the following hardware:
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* 16/24-bit Instruction Set
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* Support for FPU (Floating Point Unit)
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* Support for DSP instructions
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* 32-bit integer multiplier
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* 32-bit integer divider
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* 40-bit MAC (Multiply-Accumulate)
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The *esp-dsp* library (https://github.com/espressif/esp-dsp) provides functions written in assembly to use this hardware.
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This part describes which functions are used where in OpenCV for better performances.
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