Red Hat announced a multi-stage alliance to offer customers a greater choice of operating systems to run on Oracle Cloud Infrastructure (OCI).
Continuum Analytics announced a technical collaboration with Intel resulting in the Intel Distribution for Python powered by Anaconda.
Intel Distribution for Python powered by Anaconda was recently announced by Intel and will be delivered as part of Intel Parallel Studio XE 2017 software development suite. With a common distribution for the Open Data Science community that increases Python and R performance up to 100X, Intel has empowered enterprises to build a new generation of intelligent applications that drive immediate business value. Combining the power of the Intel Math Kernel Library (MKL) and Anaconda’s Open Data Science platform allows organizations to build the high performance analytic modeling and visualization applications required to compete in today’s data-driven economies.
By combining two de facto standards, Intel MKL and Anaconda, into a single performance-boosted Python and R distribution, enterprises can meet and exceed performance targets for next-generation data science applications. The platform includes packages and technology that are accessible for beginner Python developers, however powerful enough to tackle data science projects for big data. Anaconda offers support for advanced analytics, numerical computing, just-in-time compilation, profiling, parallelism, interactive visualization, collaboration and other analytic needs.
“While Python has been widely used by data scientists as an easy to use programming language, it was often at the expense of performance,” said Mike Lee, Technical, Enterprise and Cloud Compute Segment Manager, Developer Products Division at Intel Corporation. “The Intel Distribution for Python powered by Anaconda, provides multiple methods and techniques to accelerate and scale Python applications to achieve near native code performance.”
With the out-of-box distribution, Python applications immediately realize gains and can be tuned to optimize performance using the Intel VTune Amplifier performance profiler. Python workloads can take advantage of multi-core Intel architectures and clusters using parallel thread scheduling and efficient communication with Intel MPI and Anaconda Scale through optimized Intel Performance Libraries and Anaconda packages.
“Our focus on delivering high performance data science deployments to enterprise customers was a catalyst for the collaboration with Intel who is powering the smart and connected digital world,” said Michele Chambers, EVP of Anaconda & CMO at Continuum Analytics. “Today’s announcement of Intel’s Python distribution based on Anaconda, illustrates both companies’ commitment to empowering Open Data Science through a common distribution that makes it easy to move intelligent applications from sandboxes to production environments.”
The Intel Distribution for Python powered by Anaconda is designed for everyone from seasoned high-performance developers to data scientists looking to speed up workflows and deliver an easy to install, performance-optimized Python experience to meet enterprise needs. The collaboration enables users to accelerate Python performance on modern Intel architectures, adding simplicity and speed to applications through Intel’s performance libraries. This distribution makes it easy to install packages using conda and pip and access individual Intel-optimized packages hosted on Anaconda Cloud through conda.
- Anaconda Distribution that has been downloaded over 3M times and is the de facto standard Python distribution for Microsoft Azure ML and Cloudera Hadoop
- Intel Math Kernel performance-accelerated Python computation packages like NumPy, SciPy, scikit-learn
- Anaconda Scale, which makes it easy to parallelize workloads using Directed Acyclic Graphs (DAGs)
Intel Distribution for Python powered by Anaconda is delivered as part of the Intel Parallel Studio XE 2017. The new distribution is available for free and includes forum support.