ARCHER/RDF Overview. How do they fit together? Andy Turner, EPCC
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1 ARCHER/RDF Overview How do they fit together? Andy Turner, EPCC
2
3 Outline ARCHER/RDF Layout Available file systems Compute resources ARCHER Compute Nodes ARCHER Pre/Post-Processing (PP) Nodes RDF Data Analytic Cluster (DAC) Data transfer resources ARCHER Login Nodes ARCHER PP Nodes RDF Data Transfer Nodes (DTNs)
4 ARCHER and RDF
5 ARCHER UK National Supercomputer Large parallel compute resource Cray XC30 system 118,080 Intel Xeon cores High performance interconnect Designed for large parallel calculations Two file systems /home Store source code, key project data, etc. /work Input and output from calculations, not long-term storage
6 RDF Large scale data storage (~20 PiB) For data under active use, i.e. not an archive Multiple file systems available depending on project Modest data analysis compute resource Standard Linux cluster High-bandwidth connection to disks Data transfer resources
7 Terminology ARCHER Login Login nodes PP Serial Pre-/Post-processing nodes MOM PBS job launcher nodes /home Standard NFS file system /work Lustre parallel file system ARCHER installation is a Sonexion Lustre file system RDF DAC Data Analytic Cluster DTN Data Transfer Node GPFS General Parallel File System RDF parallel file system technology from IBM Multiple file systems available on RDF GPFs
8 Overview DTN DAC Login PP MOM Compute Nodes RDF File Systems GPFS Parallel /home NFS /work Lustre Parallel RDF ARCHER
9 Available File Systems
10 ARCHER /home Standard NFS file system Backed up daily Low-performance, limited space Mounted on: Login, PP, MOM (not Compute Nodes) /work Parallel Lustre file system No backup High performance read/write (not open/stat), large space (>4 PiB) Mounted on: Login, PP, MOM, Compute Nodes
11 RDF /epsrc, /nerc, /general Parallel GPFS file system Backed up for disaster recovery High performance (read/write/open/stat), v. large space (>20 PiB) Mounted on: DTN, DAC, Login, PP
12 Compute Resources
13 ARCHER Compute Nodes: 4920 nodes with 24 cores each (118,080 cores total) 64/128 GB memory per node Designed for parallel jobs (serial not well supported) /work file system only Accessed by batch system only PP Nodes 2 nodes with 64 cores each (256 hyperthreads in total) 1 TB memory per node Designed for serial/shared-memory jobs RDF file systems available Access directly or via batch system
14 RDF Data Analytic Cluster 12 standard compute nodes: 40 HyperThreads, 128 GB Memory 2 large compute nodes: 64 HyperThreads, 2 TB Memory Direct Infiniband connections to RDF file systems Access via batch system Designed for data-intensive workloads in parallel or serial
15 Data Transfer Resources ARCHER to/from RDF Primary resource is PP nodes Mounts ARCHER and RDF file systems Interactive data transfer can use ARCHER Login nodes Mounts ARCHER and RDF file systems Small amounts of data only To outside world RDF Data Transfer Nodes (DTNs) for large files ARCHER Login Nodes for small amounts of data only
16 Summary
17 ARCHER/RDF ARCHER and the RDF are separate systems Some RDF file systems are mounted on ARCHER login and PP nodes To enable easy data transfer (e.g. for analysis or transfer off site) A variety of file systems are available Each has its own use case Data management plan should consider which is best suited at each stage in data lifecycle Variety of compute resources available
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