Are your models scalable and running as fast as possible? Would you benefit from migrating existing models to Python?
Our team of expert computational scientists will work with you to profile your models and optimize their performance. Where appropriate, this may include a recommendation to port existing SAS, SPSS, Matlab, R or Java models to Python. By investigating library enhancements, the use of just-in-time compilers, and architectural considerations such as data flow, networking, and storage 2x to 100x, performance improvements are often possible. Scaling is a key aspect and our team will consider how your models can be parallelized and deployed effectively and efficiently across a cluster for production use.
- Speed Up - Leveraging the highest performance libraries, and considering options such as GPUs and LLVM JIT compilation of Python code, you will receive the best possible performance from your models
- Migrate - Existing SAS, SPSS, Matlab, R and Java models will be migrated to Python where appropriate
- Scale Out - Because ensuring that your models can be utilized efficiently in a cluster computing environment is essential, we will optimize them for this scenario and consider opportunities for model-internal parallelization
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