HPE Apollo Servers
Density Optimized for High-Performance Computing and Advanced Data Analytics Workloads
Hewlett Packard launched the Apollo Family of High Performance Computing systems in June 2014. They are density optimized for HPC, AI, Big Data, and more. HPE designed the Apollo Server Systems to address the needs of lightly threaded HPC applications, it offers high per-thread performance, robust network bandwidth, and rack-level shared infrastructure. They are rack-scale compute, storage, and networking solutions designed for massive scale out. With a tiered approach for organizations of all sizes, they are suitable for your big data analytics, object storage, deep learning and AI training, and other high performance computing workloads. Recent innovations in HPC technology are allowing research typically being done in government and academia accessible to enterprise customers, who are using Apollo solutions to enhance research and development efforts and gain a competitive edge.
Apollo Platform Data Sheets:




Apollo 6500 (Gen10 & Gen10+)
Do you need to increase computing performance for High Performance Computing (HPC) and Deep Learning? The HPE Apollo 6500 System is an ideal HPC and deep learning platform providing unprecedented performance with industry-leading GPUs, fast GPU interconnect, high bandwidth fabric, and a configurable GPU topology to match your workloads. The ability of computers to autonomously learn, predict, and adapt using massive data sets is driving innovation and competitive advantage across many industries and applications are driving these requirements. The system with rock-solid reliability, availability, and serviceability (RAS) features includes up to eight GPUs per server, NVLink for fast GPU-to-GPU communication, Intel® Xeon® Scalable processors support, choice of high-speed / low latency fabric, and is workload enhanced using flexible configuration capabilities. While aimed at deep learning workloads, the system is suitable for complex simulation and modeling workloads.
Apollo 6000 (Gen10)

Apollo 2000 (Gen10 & Gen10+)
More compute power in less space
Enterprise bridge to HPC scale-out architecture—in a smaller footprint that increases data center floor space while improving performance and energy consumption. A flexible, density-optimized system, HPE Apollo 2000 Gen10 System is ideal for large cloud, web services, traditional enterprise workloads, and compute intensive tasks that require high performance in a dense, scale-out form factor.
Data center optimization
The HPE Apollo 2000 Gen10 System delivers 2x density in 1U servers. Pack four 1U servers in a 2U chassis. It also offers comprehensive manageability using tools like HPE iLO5 management, HPE Apollo Platform Manager, and HPE Insight CMU.
Comprehensive server security
Only HPE offers an industry standard server with firmware level security that incorporates the Silicon Root of Trust, Commercial National Security Algorithms (CNSA), secure recovery to last known good state, and firmware run-time validation and alerts for compromised code.
- Silicon Root of Trust
- Commercial National Security Algorithms
- Secure recovery to last known good state
- Firmware runtime validation and alerts for compromised code
Flexible scale-out architecture
Mix and match servers, with ProLiant XL170r Gen10 for general purpose and ProLiant XL190r Gen10 for workloads requiring GPUs. Storage and I/O flexibility with drive mapping optimize storage allocation. Start small and grow
Apollo 20
Are you searching for more performance in a denser package?
The newly released HPE Apollo 20 System is built on the 2nd Generation Intel® Xeon® 9200 family of processors. Code-named Cascade Lake AP, these CPUs offer unmatched 2-socket performance leadership across popular workloads. Built to support both liquid-cooled and air-cooled options, the Apollo 20 System takes advantage of HPE’s strong leadership in cooling technologies as workloads continue to push power and density. The Apollo 20 System offering up to 56 cores and 12 DIMMs per socket makes it ideal for use in data-intensive industries, including oil and gas, finance, AI, manufacturing, and life sciences.