Hybridizer

Write C#.
Run on GPU.

Hybridizer compiles your .NET and Java code directly to CUDA and vectorized C++. No rewrites. No learning curve. Up to 93% of hand-tuned GPU performance.

Near-native performance from managed code

The Hybridizer operates on MSIL bytecode and Java bytecode, generating optimized source for CUDA GPUs and AVX CPUs. Your existing codebase becomes your GPU codebase.

Hand-written CUDA C++100%
Hybridizer (from C#)93%
Managed .NET (CPU only)~15%

Same code. Different target.

Decorate your C# with parallel patterns. Hybridizer handles the rest.

Your C# Code
// Standard C# with Parallel.For
Parallel.For(0, N, i =>
{
    result[i] = Math.Sqrt(a[i] * a[i] 
                + b[i] * b[i]);
});
Generated CUDA
// Auto-generated, optimized
__global__ void kernel(
    float* result, float* a, 
    float* b, int N) {
  int i = blockIdx.x * blockDim.x 
          + threadIdx.x;
  if (i < N)
    result[i] = sqrtf(a[i]*a[i] 
                + b[i]*b[i]);
}
93%
Peak GPU performance
3wk
vs. 6 months learning CUDA
0
Lines of CUDA to write
1
Codebase to maintain

Trusted by enterprise

Where compute-intensive workloads meet production deadlines.

Banking
Investment Banks
Risk engines and pricing models running 10-100x faster. Monte Carlo simulations that used to take hours, now take minutes.
Insurance
Actuarial Computing
Complex liability calculations and stochastic modeling on GPU clusters, using the same C# codebase the team already knows.
Energy
Seismic Processing
Geophysical data processing at scale. Terabytes of seismic data processed with GPU acceleration, no CUDA expertise needed.
Research
Scientific Computing
Researchers shipping GPU-accelerated simulations in weeks instead of months, staying in the language they think in.

Every .NET developer is a GPU developer

The hardware is ready. The cloud instances are waiting. The only thing missing was the bridge. Hybridizer is that bridge.