Ufora is compiled, automatically parallel python for data science and numerical computing
What is Ufora?
Ufora automates the engineering code required to run single-threaded programs in parallel across a cluster of machines. Ufora JIT compiles your Python so it's fast on a single thread, automatically detects opportunities for parallelism in your programs, and then distributes those threads and the data they access across the available RAM and CPU's in your cluster.
What it's Not
Ufora solves similar problems as paradigms like Hadoop, Spark, etc., but unlike those systems Ufora doesn't require you to work within any framework (e.g. Map Reduce) or language API's (e.g. PySpark). Our goal is that you can work natively in Python, using your existing workflow, and get significant performance benefits.
Open Source & Support
Ufora is an early-version open source project under the Apache 2.0 License. For support, contact us directly to learn about our work with enterprise customers. We're eager to hear your thoughts about this early version of the product and what additional functionality you'd like us to prioritize.
Who is Ufora?
Ufora is a team of computer scientists who wanted to tackle the challenges of distributed computing. Braxton, Ronen, Tom and group of faithful friends first came up with this new approach a few years ago and began experimenting with ways to automatically parallelize simple scripting code. The critical design goal was finding a way to reason about scripting code to figure out opportunities for parallelism of threads and data on the fly. It took years of experimentation and many false starts but now we know it's possible and we’re excited to bring it to the world to help make it a reality.