nihui

Context

I was helping a few computer science students and enthusiasts understand “how” modern processors got to be “so fast” outside of clock speed increases.

Here is the main ;p exert

Acronyms:

SIMD: Single Instruction, Multiple Data

How to update latest packages on Imagination Creator CI20 Debian 8 (jessie)

Imagination Creator CI20 board: A MIPS32 architecture evaluation board.

Creator CI20 quick start guide: PDF
eLinux: Creator CI20 board wiki

Model	Image Size	Target Size	Block Size	Total Time(sec)	GPU Memory(MB)
models-cunet	200x200	400x400	400/200/100	0.93/0.30/0.33	615/615/173
models-cunet	400x400	800x800	400/200/100	0.78/0.71/0.78	2408/615/174
models-cunet	1000x1000	2000x2000	400/200/100	3.16/3.21/3.53	2416/618/175
models-cunet	2000x2000	4000x4000	400/200/100	11.40/11.98/13.86	2420/669/193
models-cunet	4000x4000	8000x8000	400/200/100	44.33/47.15/54.76	2452/644/197
models-upconv_7_anime_style_art_rgb	200x200	400x400	400/200/100	0.16/0.16/0.15	459/459/119
models-upconv_7_anime_style_art_rgb	400x400	800x800	400/200/100	0.43/0.37/0.37	1741/460/119
models-upconv_7_anime_style_art_rgb	1000x1000	2000x2000	400/200/100	1.62/1.59/1.67	1764/462/120

Detail behind NCNN's factory pattern

NCNN adopts the factory pattern to create the layers of a nueral network. It's also the way the well-known library Caffe takes. It differs from Caffe in the implementation of the registry table. On one hand, the Caffe registry is populated in runtime as the side effect of initializion of global variable (which is a popular way for library initialization). On the other hand, the NCNN registry is determined in compile time. The registry is generated in a brilliant way using CMake instead of a hand-crafted table. NCNN's approach provides several benefits compared to Caffe's approach.

First, it's suitable for building a static library. When building a static library, the linker will strip any unused global variable to minimize the size of the library. This makes sense but it also strips the global variable which need to be inintialized to insert te layer creator into the registry. Tricky linker flags and related instrutions are required to resolve this issue. By creating

GPU Optimization for GameDev

Graphics Pipeline / GPU Architecture Overview

2011 - A trip through the Graphics Pipeline 2011
2015 - Life of a triangle - NVIDIA's logical pipeline
2015 - Render Hell 2.0
2016 - How bad are small triangles on GPU and why?
2017 - GPU Performance for Game Artists
2019 - Understanding the anatomy of GPUs using Pokémon
2020 - GPU ARCHITECTURE RESOURCES

Configure Git to use a proxy

In Brief

You may need to configure a proxy server if you're having trouble cloning or fetching from a remote repository or getting an error like unable to access '...' Couldn't resolve host '...'.

Consider something like:

	Compiling/installing the mesa virtio-venus-driver-(below done with new linux container)

	For: Chrome OS crostini-default debian container bookworm

	Best viewed in "raw" format

	In chrome browser type or paste

	chrome://flags

	$ ./benchmark/benchncnn
	thread_policy_set error 46
	loop_count = 4
	num_threads = 8
	powersave = 0
	gpu_device = -1
	cooling_down = 1
	squeezenet min = 5.64 max = 6.24 avg = 5.88
	squeezenet_int8 min = 8.93 max = 8.97 avg = 8.94
	mobilenet min = 8.86 max = 8.99 avg = 8.91

	/*!
	* Copyright (c) 2019 by Contributors
	* \file op.h
	* \brief definition of all the operators
	* \author Chuntao Hong, Xin Li
	*/

	#ifndef MXNET_CPP_OP_H_
	#define MXNET_CPP_OP_H_

	Follow the WORKAROUND:
	1. Add a comand to /etc/rc.local, add the following line above "exit 0":
	setpci -s 00:1c.2 0x50.B=0x41
	2. Add the same comand to /etc/apm/resume.d/21aspm (which does not exist yet):
	setpci -s 00:1c.2 0x50.B=0x41
	3. Add the following to /etc/modprobe.d/sdhci.conf:
	options sdhci debug_quirks2=4
	4. Re-generate initrd:
	sudo update-initramfs -u -k all
	5. Reboot or reload sdhci module: