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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Shape the future of programming languages!
CrossTL is open-source and licensed under the MIT License.
CrossGL: One Language, Infinite Possibilities 🌍
Building the universal foundation for the next generation of programming
The CrossGL Team