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Rainer HRK Series sets a new standard for 2U, upper-end mainstream servers by combining extraordinary density and versatility for both scale-up or scale-out workloads.
Rainer HRK Series is high compute and memory capacity make it ideal to maximize consolidation for Virtual Machines(VM) and container workloads to reduce sprawl and TCO (Total Cost of Ownership).
Rainer HRK Series is a great scale-up server choice for compute-intensive or memory-bound workloads, delivering outstanding performance, scalability and TCO for your more demanding needs.
3rd Gen Intel® Xeon® Scalable processors with 6 UPI and other Intel innovations integrated into the Rainer HRK Series deliver workload-optimized performance with built-in AI acceleration, and improved memory and I/O throughput versus prior generation processors.
(4)Socket, 2U Server with High Compute, Memory and Storage Capacity.
3rd Gen Intel® Xeon® Scalable processors.
Up to 28 cores per processor, 4 Sockets, for up to 112 cores per server.
Six Intel® UPI for increased CPU I/O throughput, 2x from previous generation
Intel® Optane™ persistent memory 200 series support.
Up to 15 TB system memory, 3 TB of DRAM, plus 12 TB of Intel® Optane™ persistent memory when using App Direct Mode.
(48) DIMMs total, (12) DDR4 DIMM per socket;
(1) 100GbE Intel® 800 Ethernet Series OCP3.0, 1x 1GB, RMM4 dedicated NIC.
(24) 2.5” SAS/SATA/SSD/NVMe hot-swappable drives (front access).
(2) M.2 SSDs (internal).
• Cloud
Consolidate scale out workloads; Distributed web scale cache stores that provide in-memory caching of key-value type data (Memcached, Redis, KeyDB); Containerized deployments. (Kubernetes, Red Hat OpenShift, etc.).
• Analytics
Big-data processing engines such as Apache Spark or Presto; Applications performing real-time processing of big unstructured data (financial services, Hadoop/Spark clusters); Ingest applications (typically government/ defense), where large data gets consumed, manipulated, then stored for later post-processing.
• VM /Container Density
More VMs, fewer stranded resources; Large VM (VMware, oVirt, KVM, etc.).
• In-Memory Database
In-memory databases using optimized data storage formats and analytics for business intelligence (eg: SAP HANA); Distributed web scale cache stores that provide in-memory caching of key-value type data (Memcached, Redis, KeyDB).
• Scale-Up
High-performance, relational (MySQL, Postgres, Oracle, DB2) and NoSQL (MongoDB, Cassandra) databases; Big memory high-performance computing (HPC. i.e. reservoir simulation) and Electronic Design Automation (EDA) applications.