From 8eb1cf19f78cdb21e41a606a8cef94c038f2c270 Mon Sep 17 00:00:00 2001 From: Robert Muchsel Date: Tue, 14 Jun 2022 15:05:34 -0500 Subject: [PATCH] README: Updated defaults; properly display .md in dark mode (#154) --- README.md | 27 ++++++++++++++++----------- README.pdf | Bin 6716048 -> 6707902 bytes docs/CHW.png | Bin 6203 -> 18600 bytes docs/CNNInFlight.png | Bin 121249 -> 128175 bytes docs/CNNOverview.png | Bin 380547 -> 402542 bytes docs/Conv2Dk1x1.png | Bin 586139 -> 610611 bytes docs/DataMemory.png | Bin 96919 -> 99116 bytes docs/DevelopmentFlow.png | Bin 297760 -> 185442 bytes docs/HWC.png | Bin 5960 -> 15396 bytes docs/KernelMemory.png | Bin 84231 -> 86646 bytes docs/KernelMemoryGaps.png | Bin 65554 -> 74290 bytes docs/KernelMemoryLayers.png | Bin 39609 -> 41178 bytes docs/MLP.png | Bin 554109 -> 571372 bytes docs/Numbers.png | Bin 10496 -> 20383 bytes docs/Overview.png | Bin 68239 -> 74644 bytes docs/Streaming-NextPixel.png | Bin 177101 -> 190684 bytes docs/Streaming-Rows.png | Bin 170557 -> 184094 bytes docs/Streaming.png | Bin 176550 -> 189574 bytes docs/abs.png | Bin 47684 -> 44109 bytes docs/fireexample.png | Bin 141941 -> 159505 bytes docs/fractionallystrided.png | Bin 138290 -> 146706 bytes docs/noactivation.png | Bin 57277 -> 54244 bytes docs/relu.png | Bin 39072 -> 36043 bytes docs/residual-basic.png | Bin 42601 -> 49632 bytes docs/residual.png | Bin 134914 -> 147650 bytes 25 files changed, 16 insertions(+), 11 deletions(-) diff --git a/README.md b/README.md index fda0a640e..c2030ebc1 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@ # ADI MAX78000/MAX78002 Model Training and Synthesis -June 2, 2022 +June 14, 2022 ADI’s MAX78000/MAX78002 project is comprised of five repositories: @@ -106,7 +106,7 @@ When going beyond simple models, model training does not work well without CUDA * There is a PyTorch pre-release with ROCm acceleration for certain AMD GPUs on Linux ([see blog entry](https://pytorch.org/blog/pytorch-for-amd-rocm-platform-now-available-as-python-package/)), but this is not currently covered by the installation instructions in this document, and it is not supported. -* At this time, there is neither CUDA nor ROCm nor Neural Engine support on macOS, and therefore no hardware acceleration (there is a pre-release version of PyTorch with M1 acceleration, and M1 acceleration will be supported in a future release of these tools). +* At this time, there is neither CUDA nor ROCm nor Neural Engine support on macOS, and therefore no hardware acceleration (there is a pre-release version of PyTorch with M1 acceleration on macOS 12.3 or later, and M1 acceleration will be supported in a future release of these tools). * PyTorch does not include CUDA support for aarch64/arm64 systems. *Rebuilding PyTorch from source is not covered by this document.* @@ -2147,15 +2147,18 @@ The following table describes the most important command line arguments for `ai8 | `--board-name` | Set the target board (default: `EvKit_V1`) | `--board-name FTHR_RevA` | | *Code generation* | | | | `--overwrite` | Produce output even when the target directory exists (default: abort) | | -| `--compact-data` | Use *memcpy* to load input data in order to save code space | | | `--compact-weights` | Use *memcpy* to load weights in order to save code space | | -| `--mexpress` | Use faster kernel loading | | +| `--mexpress` | Use faster kernel loading (default) | | +| `--no-mexpress` | Use alternate kernel loading (slower) | | | `--mlator` | Use hardware to swap output bytes (useful for large multi-channel outputs) | | | `--softmax` | Add software Softmax functions to generated code | | | `--boost` | Turn on a port pin to boost the CNN supply | `--boost 2.5` | | `--timer` | Insert code to time the inference using a timer | `--timer 0` | | `--no-wfi` | Do not use WFI (wait for interrupt) instructions when waiting for CNN completion | | | `--define` | Additional preprocessor defines | `--define "FAST GOOD"` | +| *MAX78002* | | | +| `--no-pipeline` | **MAX78002 only**: Disable the pipeline and run the CNN on the slower APB clock. This reduces power consumption, but increases inference time and in most cases overall energy usage. | | +| `--max-speed` | **MAX78002 only:** In pipeline mode, load weights and input data on the PLL clock divided by 1 instead of divided by 4. This is approximately 50% faster, but uses 200% of the energy compared to the default settings. | | | *File names* | | | | `--c-filename` | Main C file name base (default: main.c) | `--c-filename main.c` | | `--api-filename` | API C file name (default: cnn.c) | `--api-filename cnn.c` | @@ -2266,7 +2269,7 @@ layers: To generate an embedded MAX78000 demo in the `demos/ai85-mnist/` folder, use the following command line: ```shell -(ai8x-synthesize) $ python ai8xize.py --verbose --test-dir demos --prefix ai85-mnist --checkpoint-file trained/ai85-mnist.pth.tar --config-file networks/mnist-chw-ai85.yaml --device MAX78000 --compact-data --mexpress --softmax +(ai8x-synthesize) $ python ai8xize.py --verbose --test-dir demos --prefix ai85-mnist --checkpoint-file trained/ai85-mnist.pth.tar --config-file networks/mnist-chw-ai85.yaml --device MAX78000 --compact-data --softmax ``` *Note: For MAX78002, substitute MAX78002 as the `--device`.* @@ -2725,7 +2728,7 @@ In order to achieve this, a layer must be inserted that does nothing else but re ... layers: ... - # Layer 1 + # Layer I - out_offset: 0x0000 processors: 0x0ffff00000000000 operation: conv2d @@ -2733,14 +2736,15 @@ layers: pad: 1 activate: ReLU - # Layer 2 - re-format data with gap + # Layer II - re-format data with gap - out_offset: 0x2000 processors: 0x00000000000fffff output_processors: 0x00000000000fffff operation: passthrough write_gap: 1 + name: layerII - # Layer 3 + # Layer III - in_offset: 0x0000 out_offset: 0x2004 processors: 0x00000000000fffff @@ -2749,9 +2753,10 @@ layers: pad: 1 activate: ReLU write_gap: 1 + name: layerIII - # Layer 4 - Residual - - in_sequences: [2, 3] + # Layer IV - Residual + - in_sequences: [layerII, layerIII] in_offset: 0x2000 out_offset: 0x0000 processors: 0x00000000000fffff @@ -2964,7 +2969,7 @@ Perform minimum accelerator initialization so it can be configured or restarted. Configure the accelerator for the given network. `int cnn_load_weights(void);` -Load the accelerator weights. `cnn_init()` must be called before loading weights after reset or wake from sleep. *Note that the physical weight memories are 72-bit wide. When `--mexpress` mode is enabled, the weight data is written in a sequence of 32-bit writes, containing the “packed” weight values. When `--mexpress` is disabled, each weight memory is written in four 32-bit memory writes, with zero-padded data.* +Load the accelerator weights. `cnn_init()` must be called before loading weights after reset or wake from sleep. *Note that the physical weight memories are 72-bit wide. When `--mexpress` mode is enabled (default), the weight data is written in a sequence of 32-bit writes, containing the “packed” weight values. When using `--no-mexpress`, each weight memory is written in four 32-bit memory writes, with zero-padded data.* `int cnn_verify_weights(void);` Verify the accelerator weights (used for debug only). diff --git a/README.pdf b/README.pdf index a014e14254a58e2e1ae57066b7ad167eec60ad29..090a52403a11bc05df2e675fc3cec41d66882457 100644 GIT binary patch delta 4557203 zcmd?QWm{ZP6D67u2m}HIcZcBa4hilO+}+)^g9V46jcags3lM^9V6I)}XP+?ly| z{=xm$Ps=&`)UH~!)~ekX+_swwTdHa^&7RED@ zOI);5oSx0O-8tu7+)c&7<0VhU(aOPuOC~FCCBb<)Bkg0+MO(>vm1T7*+~JSO`M6z)yUT~ z`Q?t>&h!R5Q{5>wQ`=NtPA(!#e&oD;r+Y%2_}fl*jX1Xio5xw`lYinOpKzzsN&tU5 z!BfCqj7f3fBjf-=`O6srhEudIXVN{)3bX##Eoi`P_7;NRnCT@&dFav2$f#EX!Sj{W z@@2ZLy)JbxYD+pJy6Z2vgQXk^K}HoIhqtmhkDIX04t5A6JkJVV@3ymZ-AO%|nTbA+ zBU-}$>9aD7t)1Yr6eYW|vA`wsmGye=>7)Li-_y{4CzBPO*z%@=6(3MoC(Brwy*WH| zI6=u;cx_&I5Ai&=b0r8$b@_GK{#GlacaWP!xWV)z$?&YmGc#|(?8KqFuGqD5YOji@ zKh^B6*e|S&0Vb=UZM4LeBBGN6{G%!_-X+ikJ5O?gp0+r3y1g6rerwz_<=P&(HmKkO=XCyz})TNN@IuF|?su 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