Deep Learning Model Optimization Tools & CPU Inference Engine
Sparsify and quantize your machine learning models to minimize footprint & run on CPUs at GPU speeds.
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Learn about our community edition software components.
Sparsify is open sourced. Optimize your model today!
Open-source, easy-to-use interface to automatically sparsify and quantize deep learning models for CPUs & GPUs.
Open-source libraries and optimization algorithms for CPUs & GPUs, enabling integration with a few lines of code.
Open-source neural network model repository for highly sparse and sparse-quantized models with matching pruning recipes for CPUs and GPUs.
Free CPU runtime that runs sparse models at GPU speeds.
Paths to Sparse Acceleration
A.) Original Dense Path
Take your dense model & run it in the DeepSparse Engine, without any changes.
B.) SparseZoo Path
Take a pre-optimized model & run it in the DeepSparse Engine, or transfer learn with your data.
C.) Sparsified Path
Sparsify and quantize your dense model with ease & run it in the DeepSparse Engine.
Unprecedented Performance –– Run models on CPUs at GPU speeds. No special hardware required.
Reduce Costs –– Deploy and scale models on cheaper and more commonly available CPU servers.
Smaller Footprint –– Unlock unlimited production possibilities by reducing model footprint by 20x.
Reduce Power –– Save on energy at the edge with unique in-cache execution technology.
Run Anywhere –– Run on premise, in the cloud, or at the edge, with both CPUs and GPUs.
Easy to Use –– Eliminate trial and error. Analyze, sparsify, and fine-tune models with a few clicks.