Why IBM Spectrum Computing?

IBM Spectrum Computing uses intelligent workload and policy-driven resource management to optimise resources across the data center, on premises and in the cloud. Now scalable to over 160,000 cores, IBM provides you with the latest advances in software-defined computing technology to help you unleash the power of your distributed, mission-critical, high-performance computing (HPC) infrastructure. You gain up to 150x faster big data analytics applications and new generation open source frameworks such as Hadoop and Spark.

Try before you buy. See how IBM Spectrum Computing reduces costs and accelerates time to results.

Optimised for compute- and data-intensive workloads

IBM Spectrum LSF

Comprehensive workload management solution. Simplify HPC with an enhanced user and administrator experience, reliability, and performance at scale.

IBM Spectrum MPI

High-performance, production-quality implementation of Message Passing Interface (MPI). Accelerate application performance in distributed computing environments.

IBM Spectrum Cluster Foundation

No-charge infrastructure lifecycle management solution for scale-out environments. Gain systems deployment and advanced software management.

IBM High Performance Services

HPC and storage clusters as a service in the Softlayer cloud. Meet new and peak HPC demands quickly and economically.

New generation

Are you adopting a new generation of technologies such as Apache Spark, noSQL databases and containers to accelerate insights from all your data? Traditional IT server configurations, hypervisor environments and storage silos do not work well for these modern approaches because they are not optimised for distributed computing.

IBM Spectrum Conductor with Spark solves this challenge with software-defined infrastructure technology designed for distributed environments. Now you can deploy Apache Spark efficiently and effectively, and support multiple versions and instances of Spark along with a broad set of born-in-the-cloud application frameworks.

High-performance analytics

IBM Spectrum Symphony

Optimise your big data analytics applications. IBM Spectrum Symphony is highly scalable, high-throughput, low-latency workload and resource management software for compute- and data-intensive analytics applications.

IBM Spectrum Symphony can reallocate more than 1,000 compute engines per second to different workloads and, with sub-millisecond overhead per task, provides throughput of up to 17,000 tasks per second.

IBM High Performance Services for Analytics

Quickly and economically meet new and peak HPC demands. IBM High Performance Services provides HPC and storage clusters in the Softlayer cloud. Fully functioning and ready-to-use hybrid and stand-alone clusters are securely connected to your on-premises cluster.

You gain automatic job transfer and control for seamless workload management. A dedicated Cloud Operations team delivers design, installation, configuration and 24-hour support.

Solutions to today’s most demanding HPC challenges


Enable your high-performance application users to benefit from the advantages of private, hybrid and public clouds

Cluster Management

Simplify the entire cluster management process, improve performance and optimise resources with this no-charge solution

Big data and analytics

Build your big data strategy on a solid, high-performance foundation that delivers flexibility and long-term value

Workload Management

Increase productivity and reduce costs with workload management designed for demanding, distributed HPC environments

What’s new

Accelerate Science and Engineering

Learn how to drive productivity and maximise the utilisation and value of your HPC infrastructure with new IBM Spectrum LSF 10.1

Spark for Dummies

Learn about the state of big data today, along with how Spark can streamline and simplify the ways you interact with and extract value from it.

Boost your Big Data Analytics

Learn how to optimise your big data analytics infrastructure for performance, flexibility and long-term value. Get insights and best practices from IDC Research VP Carl Olofson on deploying Spark in a production environment.