Eshi 🧑‍🎨 (絵師)

A high-performance, hybrid CPU/GPU shader engine and video generator.

Warp

🖼️ Showcase

Aurora	Deep Sea	Fractal
Polar	Raymarch	Ripple
Starfield	Tzozen	Voronoi
Bubbles	Neon	Seascape

Eshi (Japanese for "painter" or "artist") is a minimal C++ framework that turns mathematical formulas into video. It allows you to write GLSL-style logic directly in C++, rendering procedural art to high-quality video files (.mp4) or a live window preview.

"Painting pixels with math." 🥴🍹💫 -me

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🎨 Origins & Credits

This project is heavily inspired by and builds upon the foundational concepts of Tzozen's checker.c.

Eshi evolves this concept by embedding the encoding pipeline directly into the application, supporting multi-threaded CPU rendering (OpenMP), GPU acceleration (CUDA & OpenGL), and live previews (SDL2).

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✨ Features

• Hybrid Rendering: Seamlessly switch between CPU (OpenMP), GPU (CUDA/OpenGL), and GPU (Metal) rendering engines.
• Live Preview: Tweak your shaders in real-time with an SDL2 window (--live).
• Zero-IO Video: Renders directly to H.264 (.mp4) in memory using linked FFmpeg libraries.
• Modern CLI: Beautiful terminal UI powered by Gum.
• C++ Shaders: A robust math library (glsl_core.h) that emulates GLSL types (vec2, vec4) and intrinsics in standard C++.
• Zig Shader Examples: Link Zig implementations into the CPU renderer while using portable GPU companions for accelerated rendering.
• Arm64 Support: Native compilation and hardware acceleration on Windows on Arm (Snapdragon) devices.

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🛠️ Build & Dependencies

🐧 Linux (Debian/Ubuntu/Arch)

1. System Libraries:

# Core Dependencies
sudo apt install pkg-config libavcodec-dev libavformat-dev libavutil-dev libswscale-dev libomp-dev libsdl2-dev

# Install Gum (for the CLI dashboard)
sudo mkdir -p /etc/apt/keyrings
curl -fsSL [https://repo.charm.sh/apt/gpg.key](https://repo.charm.sh/apt/gpg.key) | sudo gpg --dearmor -o /etc/apt/keyrings/charm.gpg
echo "deb [signed-by=/etc/apt/keyrings/charm.gpg] [https://repo.charm.sh/apt/](https://repo.charm.sh/apt/) * *" | sudo tee /etc/apt/sources.list.d/charm.list
sudo apt update && sudo apt install gum

2. Fetch libsumi:

./vendor.sh
# or: make vendor

If you are actively developing libsumi in a sibling checkout, skip vendoring and pass it directly:

make SUMI_PATH=../libsumi -j$(nproc)

By default, the Makefile uses ./libsumi when it exists and falls back to ../libsumi for local libsumi development.

3. Compile:

make -j$(nproc)

(Note: If nvcc is found in your PATH, Eshi automatically compiles with CUDA support.)

Troubleshooting CUDA Paths: If the build fails with /usr/bin/ld: cannot find -lcudart, your CUDA installation may be in a non-standard location (common on Arch/CachyOS). You can fix this by editing the CUDA_PATH_LINUX variable at the top of the Makefile, or by passing it directly to make:

# Example for Arch Linux / CachyOS
make CUDA_PATH_LINUX=/opt/cuda -j$(nproc)

🍎 macOS (Homebrew)

1. System Libraries:

brew install pkg-config ffmpeg sdl2 sdl2_ttf libomp zlib bzip2 freetype

2. Fetch libsumi:

./vendor.sh
# or: make vendor

3. Compile:

make -j$(sysctl -n hw.ncpu)

The Makefile automatically prepends Homebrew pkg-config paths for keg-only and macOS shim dependencies such as zlib and bzip2.

The Makefile uses zig c++ by default. (zig cc can infer C++ from a .cpp input, but it does not select the C++ runtime when it performs the final link.) You can still select another C++ compiler explicitly:

make CXX=clang++

Independent Zig build

The native Zig build graph produces the same main program and examples under zig-out/bin:

# Everything, optimized with ReleaseFast by default
zig build

# Only one artifact
zig build eshi
zig build warp
zig build harlequin

# Useful overrides
zig build eshi -Doptimize=Debug -Dopenmp=false
zig build eshi -Dsumi-path=../libsumi

Both build paths use pkg-config for SDL2 and FFmpeg. On macOS, the Zig build enables Metal and uses Homebrew's libomp; override a nonstandard installation with -Dlibomp-prefix=/path/to/libomp. Outside macOS the Zig build currently exercises the CPU/OpenMP path; CUDA auto-detection remains in the Makefile path.

Shader examples may implement the CPU entry point in Zig. Because GPU drivers cannot execute that host object directly, those examples provide a matching portable GPU companion at examples/gpu/<name>.cpp. Eshi selects the companion automatically for --gpu; the same source is consumed by Metal, OpenGL, and CUDA backends. The --gpu flag does not generate or emit this .cpp file: the companion is checked into the repository as shader source for GPU compilers.

For example, harlequin links examples/harlequin.zig for CPU rendering and loads examples/gpu/harlequin.cpp when --gpu selects a GPU backend:

make build/harlequin
./build/harlequin --live --gpu

Zig 0.16 cannot use LTO for Mach-O: Zig requires LLD for LTO, while its LLD backend cannot link Mach-O. Consequently, both Zig-based paths disable LTO on macOS. -fuse-ld=lld does not work around this. On other platforms LTO remains enabled by default; disable it with make USE_LTO=0 or zig build -Dlto=false.

For isolated build/runtime benchmarks, use different prefixes so neither path can reuse or overwrite the other's artifacts:

make BUILD_DIR=build-make -j$(sysctl -n hw.ncpu)
zig build -p build-zig

# Example with hyperfine installed; benchmark the same renderer and arguments.
hyperfine './build-make/warp --res 320x180' './build-zig/bin/warp --res 320x180'

For cold build-time measurements, also give each command a different ZIG_GLOBAL_CACHE_DIR; separate output directories do not separate Zig's compiler cache.

To remove Make outputs and Zig's default local artifacts (.zig-cache and zig-out), run:

make clean

If you supplied custom BUILD_DIR, ZIG_CACHE_DIR, or ZIG_OUT_DIR values, pass the same values to make clean.

🪟 Windows (x64)

1. Prerequisites:

• Visual Studio (MSVC C++ Compiler)
• CUDA Toolkit (Must be installed and nvcc reachable)
• vcpkg package manager

2. Install Dependencies: Open a terminal in the project root and run:

vcpkg install --triplet x64-windows

3. Configure & Compile:

1. Open build_all.bat in a text editor.
2. Update VCPKG_ROOT and CUDA_PATH variables.
3. Run build_all.bat.

🐲 Windows (Arm64 / Snapdragon)

1. Prerequisites:

• Visual Studio 2022 (Ensure "ARM64 build tools" are installed)
• vcpkg package manager
• OpenCL™ and OpenGL® Compatibility Pack (Install from Microsoft Store to enable Adreno GPU support)

2. Install Dependencies: Open a terminal in the project root and run:

vcpkg install --triplet arm64-windows

3. Configure & Compile:

1. Open the ARM64 Native Tools Command Prompt for VS 2022.
2. Open build.arm64.bat and update VCPKG_ROOT.
3. Run the build script:

   build.arm64.bat

4. Executables will be generated in build/.

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🚀 Usage

1. The Interactive Dashboard (Recommended)

The easiest way to run demos is with the beautified shell script (Linux/WSL only currently):

./run_demos.sh

This launches a GUI-like menu in your terminal to select CPU/GPU modes and shows progress bars for renders.

2. Manual CLI

You can also run the built binaries directly from the build/ folder:

Render to Video:

# Linux
./build/deepsea
# Windows
.\build\deepsea.exe

# Output: deepsea.mp4 (in build/)

Live Preview:

./build/deepsea --live
# Opens a window. Press ESC to close.

Options:

• --gpu: Use hardware acceleration (CUDA on x64, OpenGL on Arm64).
• --live: Render to window instead of file.
• --res WxH: Set resolution (e.g., --res 1920x1080). Default is 960x540.

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🧑‍💻 Writing Shaders

Define your art in shader.cpp using the mainImage function (Shadertoy style):

void mainImage(vec4 &fragColor, vec2 fragCoord, vec2 iResolution, float iTime) {
    vec2 uv = fragCoord / iResolution.y;
    // ... your GLSL logic here ...
    fragColor = vec4(uv.x, uv.y, 0.5f + 0.5f*sinf(iTime), 1.0f);
}

Rebuild to update the binary.

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🏛️ License

This project retains the MIT License of the original code.

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📝 Finally

З.Ы. Если вы дочитали до этого места, буду благодарен за звезду!

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🥂 За здоровье!