Machine Learning: Develop Predictive Models
As machine learning becomes a must-have for business models and forecasts, it’s important to consider frameworks that can be integrated into your big data analytics environments and workflows. The Cray Urika-GX platform is a pre-integrated hardware-software platform that includes Apache Spark™, which provides a machine-learning library, and MLlib, designed for simplicity, scalability and easy integration with other tools.
The Cray Urika-GX platform is designed to accelerate Spark machine learning tasks in a very accessible format with large in-memory compute ability, up to 22 TB DRAM, and dense cores in a standard enterprise rack.
Also included in the Urika-GX system are Hadoop® and the Cray Graph Engine so you can run all your big data analytics workflows on one system and avoid the common overhead of data movement. We also leverage open standards like OpenStack, Mesos and Docker so you can be ready for data in days and then customize for future needs.
Deep Learning: Expand Your Insight
The Cray CS-Storm accelerated GPU system is ideal for deep learning problems that require precision and performance in an accessible format. Cray has now integrated NVIDIA’s most powerful deep learning and HPC GPUs (NVIDIA® Tesla® M40 and P100) on a dense platform that provides 8x GPUs within a single server for up to 250 GPU teraflops in a single rack.
Adding support for additional NVIDIA GPU accelerators, the M40 Tesla deep learning training accelerator provides up to 7 teraflops (TF) of single precision performance, with 3,072 cores and 24 GBs of DDR 4 memory. It is optimized for emerging applications such as machine learning and deep learning.
The Tesla P100 GPU accelerator for PCIe — powered by the NVIDIA Pascal™ architecture — offers 3,584 cores and up to 16 GB of HBM2 memory to deliver up to 9.4 TF single precision or 4.7 TF double precision performance with GPU boost technology. The Tesla P100 is well suited for the most demanding research and scientific applications.
Deep learning toolkits
So customers can immediately take advantage of their high-performance CS-Storm systems without altering deep learning software models, Cray offers several validated deep learning toolkits using NVIDIA Docker images for more robust performance:
- Microsoft Cognitive Toolkit (previously CNTK)
- NVIDIA Digits
For deep neural network training, the XC50 system is the world’s most scalable deep learning supercomputer. The XC50 supercomputer features the Tesla P100 GPU accelerator for PCIe, which enables lightning-fast nodes to deliver the highest absolute performance for high performance computing and deep learning workloads. And optimizations such as partitioned global address space (PGAS) and Cray’s Aries™ supercomputing interconnect, with its all-to-all communications, support more parallel analytics at scale with higher throughput.
To simplify the building and deploying of deep learning environments in supercomputing, Cray provides XC customers with directive files for common deep learning tools, such as TensorFlow and Microsoft Cognitive Toolkit (previously CNTK).