Optimized For Workloads - IBM NeXtScale System Planning And Implementation Manual

2.1.2 Optimized for workloads

IBM NeXtScale System is best-suited for the following primary workloads:
Public and private cloud
HPC and technical computing
Although these areas do share much in common, they have unique needs that
are served with NeXtScale System, as shown in Figure 2-2.
Private Cloud
Figure 2-3 IBM NeXtScale System: Optimized for cloud computing and HPC solutions
For cloud, the important factors are that we support the entire processor stack;
so, no matter what our client goal is, we can support it with the right processor
performance and cost point. The same is true of memory; we have cost and
power-optimized choices and performance-optimized alternatives. The nodes
contain the right onboard networking on board with 1 Gb NICs embedded, with
options for up to four other high-speed fabric ports. With these features, the
entire solution is designed to scale to any size.
HPC and technical computing have many of the same attributes as cloud; a key
factor is the need for the top-bin 130 W processors. NeXtScale System can
support top bin 130 W processors, which means more cores and higher
frequencies than others.
Workload
Public Cloud
High Performance
Computing
Fine Tuned Server Characteristics
• Processor and Memory performance and choice
Intel stack support with memory for performance and/or
cost optimization
• Standard Rack optimized Fits into client data centers
seamlessly
• Right sized IO Choice of networking options – 1Gb,
10Gb, or InfiniBand, all SDN ready
• Infinitely Scalable from small to enormous grid
deployments all built on open standards
• High energy efficiency means more impact/watt
• Top bin Intel Xeon processors, large memory
bandwidth, and high IOPS for rapid transaction
processing and analytics
• Workload optimized software stack
Computing and IBM xCAT
• Architected for low latency with choice of high speed
fabric support
• Supported as one part number no matter the size of
the solution and content with Intelligent Cluster
Chapter 2. Positioning
Full
with Platform
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