What is SOL?
SOL is an AI compiler platform that accelerates and optimizes AI workloads. It serves as a replacement for other compilers, boosting performance and reducing memory and compute overhead without requiring hardware or software changes. |
Why SOL?
SOL bridges the gap between advanced hardware and AI frameworks, offering seamless integration with existing AI infrastructure, high optimization and excellent hardware and software compatibility, helping transform your hardware into AI-ready systems. |
Why is it better than other compilers?
SOL has a faster, more efficient auto-tuning phase than Apache TVM and can outperform other commonly used compilers. It maintains high accuracy without using quantization and delivers mathematically equivalent results through smart optimization. |
With which AI frameworks is SOL compatible?
SOL supports major AI frameworks such as NumPy, TensorFlow and PyTorch, thanks to its framework-agnostic design. Further, SOL supports loading ONNX models and retrains them in TensorFlow or PyTorch. It also allows cross-framework execution and supports training, inferences and deployment without bloated dependencies. |
Which hardware does SOL support?
SOL works with a variety of hardware platforms, offering native, hybrid and offload AI execution modes. Its hardware-agnostic design helps ensure broad compatibility and easily extendible platforms. New hardware can be supported by adding hardware plugins for SOL. |
How do I get started using SOL?
If you're an AI engineer, you can start by adding SOL as a package in your python code. If you’re a hardware producer, you can start using SOL by substituting it for your current compiler. |
To find out more or start using SOL, reach out to us via info@neclab.eu to schedule a SOL introduction call.