CrossTL is a revolutionary universal programming language translator built around CrossGL - a powerful intermediate representation (IR) language that serves as the bridge between diverse programming languages, platforms, and computing paradigms. More than just a translation tool, CrossGL represents a complete programming language designed for universal code portability and cross-platform development.
CrossGL has evolved far beyond its origins as a shader language into a comprehensive programming language with full support for:
- Advanced Control Flow: Complex conditionals, loops, switch statements, and pattern matching
- Rich Data Structures: Arrays, structs, enums, and custom types
- Memory Management: Buffer handling, pointer operations, and memory layout control
- Function Systems: First-class functions, generics, and polymorphism
- Compute Paradigms: Parallel processing, GPU computing, and heterogeneous execution
- Modern Language Features: Type inference, pattern matching, and algebraic data types
CrossGL enables you to write sophisticated programs once and deploy across:
- Graphics APIs: Metal, DirectX (HLSL), OpenGL (GLSL), Vulkan (SPIRV)
- Systems Languages: Rust, Mojo
- GPU Computing: CUDA, HIP
- Specialized Domains: Slang (real-time graphics), compute shaders
CrossTL provides comprehensive bidirectional translation between CrossGL and major programming ecosystems:
- Metal - Apple's unified graphics and compute API
- DirectX (HLSL) - Microsoft's graphics framework
- OpenGL (GLSL) - Cross-platform graphics standard
- Vulkan (SPIRV) - High-performance graphics and compute
- Rust - Memory-safe systems programming with GPU support
- Mojo - AI-first systems language with Python compatibility
- CUDA - NVIDIA's parallel computing platform
- HIP - AMD's GPU computing interface
- Slang - Real-time shading and compute language
- CrossGL (.cgl) - Our universal programming language and IR
- 🔄 Universal Portability: Write complex algorithms once, run on any platform
- ⚡ Performance Preservation: Maintain optimization opportunities across translations
- 🧠 Simplified Development: Master one language instead of platform-specific variants
- 🔍 Advanced Debugging: Universal tooling for analysis and optimization
- 🔮 Future-Proof Architecture: Easily adapt to emerging programming paradigms
- 🌐 Bidirectional Translation: Migrate existing codebases to CrossGL or translate to any target
- 📈 Scalable Complexity: From simple shaders to complex distributed algorithms
- 🎯 Domain Flexibility: Graphics, AI, HPC, systems programming, and beyond
CrossTL employs a sophisticated multi-stage translation pipeline:
- Lexical Analysis: Advanced tokenization with context-aware parsing
- Syntax Analysis: Robust AST generation with error recovery
- Semantic Analysis: Type checking, scope resolution, and semantic validation
- IR Generation: Conversion to CrossGL intermediate representation
- Optimization Passes: Platform-agnostic code optimization and analysis
- Target Generation: Backend-specific code generation with optimization
- Post-Processing: Platform-specific optimizations and formatting
CrossGL supports seamless translation in both directions - import existing code from any supported language or export CrossGL to any target platform.
// Advanced pattern matching and algebraic data types enum Result<T, E> { Ok(T), Error(E) } struct Matrix<T> { data: T[], rows: u32, cols: u32 } function matrixMultiply<T>(a: Matrix<T>, b: Matrix<T>) -> Result<Matrix<T>, String> { if (a.cols != b.rows) { return Result::Error("Matrix dimensions incompatible"); } let result = Matrix<T> { data: new T[a.rows * b.cols], rows: a.rows, cols: b.cols }; parallel for i in 0..a.rows { for j in 0..b.cols { let mut sum = T::default(); for k in 0..a.cols { sum += a.data[i * a.cols + k] * b.data[k * b.cols + j]; } result.data[i * result.cols + j] = sum; } } return Result::Ok(result); } // GPU compute shader with advanced memory management compute spawn matrixCompute { buffer float* matrix_A; buffer float* matrix_B; buffer float* result; local float shared_memory[256]; void main() { let idx = workgroup_id() * workgroup_size() + local_id(); // Complex parallel reduction with shared memory shared_memory[local_id()] = matrix_A[idx] * matrix_B[idx]; workgroup_barrier(); // Tree reduction for stride in [128, 64, 32, 16, 8, 4, 2, 1] { if (local_id() < stride) { shared_memory[local_id()] += shared_memory[local_id() + stride]; } workgroup_barrier(); } if (local_id() == 0) { result[workgroup_id()] = shared_memory[0]; } } }// Physically-based rendering with advanced material system struct Material { albedo: vec3, metallic: float, roughness: float, normal_map: texture2d, displacement: texture2d } struct Lighting { position: vec3, color: vec3, intensity: float, attenuation: vec3 } shader PBRShader { vertex { input vec3 position; input vec3 normal; input vec2 texCoord; input vec4 tangent; uniform mat4 modelMatrix; uniform mat4 viewMatrix; uniform mat4 projectionMatrix; output vec3 worldPos; output vec3 worldNormal; output vec2 uv; output mat3 TBN; void main() { vec4 worldPosition = modelMatrix * vec4(position, 1.0); worldPos = worldPosition.xyz; vec3 T = normalize(vec3(modelMatrix * vec4(tangent.xyz, 0.0))); vec3 N = normalize(vec3(modelMatrix * vec4(normal, 0.0))); vec3 B = cross(N, T) * tangent.w; TBN = mat3(T, B, N); worldNormal = N; uv = texCoord; gl_Position = projectionMatrix * viewMatrix * worldPosition; } } // Advanced fragment shader with PBR lighting fragment { input vec3 worldPos; input vec3 worldNormal; input vec2 uv; input mat3 TBN; uniform Material material; uniform Lighting lights[8]; uniform int lightCount; uniform vec3 cameraPos; output vec4 fragColor; vec3 calculatePBR(vec3 albedo, float metallic, float roughness, vec3 normal, vec3 viewDir, vec3 lightDir, vec3 lightColor) { // Advanced PBR calculation with microfacet model vec3 halfVector = normalize(viewDir + lightDir); float NdotV = max(dot(normal, viewDir), 0.0); float NdotL = max(dot(normal, lightDir), 0.0); float NdotH = max(dot(normal, halfVector), 0.0); float VdotH = max(dot(viewDir, halfVector), 0.0); // Fresnel term vec3 F0 = mix(vec3(0.04), albedo, metallic); vec3 F = F0 + (1.0 - F0) * pow(1.0 - VdotH, 5.0); // Distribution term (GGX) float alpha = roughness * roughness; float alpha2 = alpha * alpha; float denom = NdotH * NdotH * (alpha2 - 1.0) + 1.0; float D = alpha2 / (3.14159 * denom * denom); // Geometry term float G = geometrySmith(NdotV, NdotL, roughness); vec3 numerator = D * G * F; float denominator = 4.0 * NdotV * NdotL + 0.001; vec3 specular = numerator / denominator; vec3 kS = F; vec3 kD = vec3(1.0) - kS; kD *= 1.0 - metallic; return (kD * albedo / 3.14159 + specular) * lightColor * NdotL; } void main() { vec3 normal = normalize(TBN * (texture(material.normal_map, uv).rgb * 2.0 - 1.0)); vec3 viewDir = normalize(cameraPos - worldPos); vec3 color = vec3(0.0); for (int i = 0; i < lightCount; ++i) { vec3 lightDir = normalize(lights[i].position - worldPos); float distance = length(lights[i].position - worldPos); float attenuation = 1.0 / (lights[i].attenuation.x + lights[i].attenuation.y * distance + lights[i].attenuation.z * distance * distance); vec3 lightColor = lights[i].color * lights[i].intensity * attenuation; color += calculatePBR(material.albedo, material.metallic, material.roughness, normal, viewDir, lightDir, lightColor); } // Add ambient lighting color += material.albedo * 0.03; // Tone mapping and gamma correction color = color / (color + vec3(1.0)); color = pow(color, vec3(1.0/2.2)); fragColor = vec4(color, 1.0); } } }Install CrossTL's universal translator:
pip install crosstl// algorithm.cgl - Universal algorithm implementation function quicksort<T>(arr: T[], low: i32, high: i32) -> void { if (low < high) { let pivot = partition(arr, low, high); quicksort(arr, low, pivot - 1); quicksort(arr, pivot + 1, high); } } function partition<T>(arr: T[], low: i32, high: i32) -> i32 { let pivot = arr[high]; let i = low - 1; for j in low..high { if (arr[j] <= pivot) { i++; swap(arr[i], arr[j]); } } swap(arr[i + 1], arr[high]); return i + 1; } compute parallel_sort { buffer float* data; uniform int size; void main() { let idx = global_id(); if (idx < size) { // Parallel bitonic sort implementation bitonicSort(data, size, idx); } } }import crosstl # Translate to any target language/platform rust_code = crosstl.translate('algorithm.cgl', backend='rust', save_shader='algorithm.rs') cuda_code = crosstl.translate('algorithm.cgl', backend='cuda', save_shader='algorithm.cu') metal_code = crosstl.translate('algorithm.cgl', backend='metal', save_shader='algorithm.metal') mojo_code = crosstl.translate('algorithm.cgl', backend='mojo', save_shader='algorithm.mojo')import crosstl # Translate neural network kernels across AI platforms ai_kernel = """ compute neuralNetwork { buffer float* weights; buffer float* inputs; buffer float* outputs; buffer float* biases; uniform int input_size; uniform int output_size; void main() { let neuron_id = global_id(); if (neuron_id >= output_size) return; float sum = 0.0; for i in 0..input_size { sum += weights[neuron_id * input_size + i] * inputs[i]; } outputs[neuron_id] = relu(sum + biases[neuron_id]); } } """ # Deploy across AI hardware platforms cuda_ai = crosstl.translate(ai_kernel, backend='cuda') # NVIDIA GPUs hip_ai = crosstl.translate(ai_kernel, backend='hip') # AMD GPUs metal_ai = crosstl.translate(ai_kernel, backend='metal') # Apple Silicon mojo_ai = crosstl.translate(ai_kernel, backend='mojo') # Mojo AI runtime# Translate systems-level code across platforms systems_code = """ struct MemoryPool { buffer u8* memory; size_t capacity; size_t used; mutex lock; } function allocate(pool: MemoryPool*, size: size_t) -> void* { lock_guard guard(pool.lock); if (pool.used + size > pool.capacity) { return null; } void* ptr = pool.memory + pool.used; pool.used += size; return ptr; } """ rust_systems = crosstl.translate(systems_code, backend='rust') # Memory-safe systems code cpp_systems = crosstl.translate(systems_code, backend='cpp') # High-performance C++ c_systems = crosstl.translate(systems_code, backend='c') # Portable C code# Import and unify existing codebases conversions = [ ('existing_shader.hlsl', 'unified.cgl'), # DirectX to CrossGL ('gpu_kernel.cu', 'unified.cgl'), # CUDA to CrossGL ('graphics.metal', 'unified.cgl'), # Metal to CrossGL ('algorithm.rs', 'unified.cgl'), # Rust to CrossGL ('compute.mojo', 'unified.cgl'), # Mojo to CrossGL ] for source, target in conversions: unified_code = crosstl.translate(source, backend='cgl', save_shader=target) print(f"✅ Unified {source} into CrossGL: {target}")import crosstl # One CrossGL program, unlimited platforms program = 'universal_algorithm.cgl' # Deploy across all supported platforms deployment_targets = { # Graphics APIs 'metal': '.metal', # Apple ecosystems 'directx': '.hlsl', # Windows/Xbox 'opengl': '.glsl', # Cross-platform 'vulkan': '.spirv', # High-performance # Systems languages 'rust': '.rs', # Memory safety 'mojo': '.mojo', # AI-optimized 'cpp': '.cpp', # Performance 'c': '.c', # Portability # Parallel computing 'cuda': '.cu', # NVIDIA 'hip': '.hip', # AMD 'opencl': '.cl', # Cross-vendor # Specialized 'slang': '.slang', # Real-time graphics 'wgsl': '.wgsl', # Web platforms } for backend, extension in deployment_targets.items(): output_file = f'deployments/{program.stem}_{backend}{extension}' try: code = crosstl.translate(program, backend=backend, save_shader=output_file) print(f"✅ {backend.upper()}: {output_file}") except Exception as e: print(f"⚠️ {backend.upper()}: {str(e)}") print(f"\n🚀 Universal deployment complete!") print(f"📁 Check deployments/ directory for platform-specific implementations")CrossGL provides comprehensive programming language features:
- Strong static typing with type inference
- Generic programming with type parameters
- Algebraic data types (enums with associated data)
- Trait/interface system for polymorphism
- Memory layout control for performance
- Pattern matching for complex conditional logic
- Advanced loops (for, while, loop with break/continue)
- Exception handling with Result types
- Async/await for concurrent programming
- Explicit lifetime management when needed
- Buffer abstractions for GPU programming
- Pointer safety with compile-time checks
- Reference semantics for efficient data sharing
- Compute shaders for GPU programming
- Parallel loops for CPU vectorization
- Workgroup operations for GPU synchronization
- Memory barriers for consistency
For comprehensive language documentation, visit our Language Reference.
CrossGL is a community-driven project. Whether you're contributing language features, backend implementations, optimizations, or documentation, your contributions shape the future of universal programming! 🌟
Find out more in our Contributing Guide
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CrossTL is open-source and licensed under the Apache License 2.0.
CrossGL: One Language, Infinite Possibilities 🌍
Building the universal foundation for the next generation of programming
The CrossGL Team