Product - How Hybridizer Works
Transform your existing C# code into high-performance GPU applications without learning CUDA. See exactly how simple it is.
Simple C# to GPU in 3 Steps
1
Write Normal C# Code
Use your existing .NET skills. No special GPU syntax required.
2
Add Simple Attributes
Mark methods for GPU execution with [EntryPoint] attribute.
3
Run on GPU
Hybridizer generates optimized CUDA code automatically.
// mark as a kernel
[EntryPoint()]
public static void Run(int N, double[] a, double[] b)
{
Parallel.For(0, N, i => { a[i] += b[i]; });
}
// create a wrapper object to call GPU methods instead of C#
HybRunner runner = HybRunner.Cuda();
dynamic wrapped = runner.Wrap(new Program());
// run the method on GPU
wrapped.Run(N, array2, array1);
// run .Net method on CPU
Run(N, array3, array1);
Hybridizer vs Traditional CUDA Development
Traditional CUDA
Hybridizer
Learning Curve
6+ months to master
Use existing C# skills
Code Complexity
Memory management, kernels
Simple attributes
Debugging
Limited tools
Full Visual Studio debugging
Time to Production
3-6 months
2-3 weeks
Performance
100% (hand-optimized)
Up to 87% (auto-optimized)
Team Scalability
Requires CUDA experts
Any .NET developer
Maintenance
Complex, error-prone
Standard C# maintenance
Proven Performance Results
83%
of hand-written CUDA performance
Average across all benchmarks
90%
reduction in development time
Compared to learning CUDA
Enterprise Features
- Full source code generation (CUDA, AVX)
- 24/7 enterprise support
- Code auditing and optimization consulting
Ready to Accelerate Your .NET Applications?
Join 3000+ developers who've already made the switch to GPU computing without CUDA complexity.
Free Community Edition available • No credit card required