IBM Introduces New Software to Ease Adoption of AI, Machine Learning and Deep Learning Posted on : Nov 19 - 2017

IBM announced new software to deliver faster time to insight for high performance data analytics (HPDA) workloads, such as Spark, Tensor Flow and Caffé, for AI, Machine Learning and Deep Learning. Based on the same software, which will be deployed for the Department of Energy’s CORAL Supercomputer Project at both Oak Ridge and Lawrence Livermore, IBM will enable new solutions for any enterprise running HPDA workloads.

New to this launch is Deep Learning Impact (DLI), a set of software tools to help users develop AI models with the leading open source deep learning frameworks, like TensorFlow and Caffe.  The DLI tools are complementary to the PowerAI deep learning enterprise software distribution already available from IBM. Also new is web access and simplified user interfaces for IBM Spectrum LSF Suites, combining a powerful workload management platform with the flexibility of remote access. Finally, the latest version of IBM Spectrum Scale software ensures support to move workloads such as unified file, object and HDFS from where it is stored to where it is analyzed.

Through this new software IBM is delivering users a set of comprehensive, open offerings developed to speed adoption and production of parallel processing and clustered computing through offerings designed to:

Simplify deployment – cluster virtualization to make many systems work together as one with easy to deploy packages that support multiple applications, users and departments on shared compute and data services designed to rapidly manage clusters for HPC and deep learning/machine learning;

Deliver AI for the enterprise – from centralized management and reporting, multitenant access, and end-to-end security, to full IBM support and services, our offerings have been designed to offer the level of function and support expected in an enterprise data center;

Ease adoption of cognitive workloads – end users can access and use cluster resources across more applications, lowering the need for specialized cluster knowledge;

Provide elasticity to hybrid cloud – simplifying cloud usage in distributed clustered environments with automated workload driven cloud provisioning and de-provisioning, so you only pay for what you use, and intelligent workload and data transfer to and from the cloud, making cloud usage transparent to the end user;

Open for the latest technology – IBM storage software supports the latest Open Source tools and protocols allowing the future adoption of Containers, Spark, or other modules like Deep Learning. View More