DMF & Tiering Update. Kirill Malkin Director of Storage Engineering. September 2015

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Transcription:

DMF & Tiering Update Kirill Malkin Director of Storage Engineering September 2015 1

What s New in DMF? Data Migration Facility (DMF) Data management solution for HPC/HPDA Over 20 years of data management High performance parallel data movement 0.5EB of storage, some sites over 100PB Potential to grow by a magnitude over next 2 years DMF for Lustre Transparent integration with Lustre HSM Eliminates intermediate copy operation Tiered Data on UV Data tiering solution for Flash on UV High-density cold storage on disks 2

Seamless Tiered Data Management The Result: Infinitely Scalable Lustre The most recent and active data is live in Lustre and mirrored to the HSM, but ALL DATA APPEARS ONLINE to users Overflow data is stored and protected within DMF on various cost-correct media types 3

EXTEND EXTEND Seamless Tiered Data Management Lustre Client Lustre Client Lustre Client Lustre Client Lustre Client Lustre Client Lustre Storage Environment MDS / MDT OSS / OST OSS / OST OSS / OST OSS / OST OSS / OST MDS / MDT Flash - Disk DMF Lustre HSM and Data Management Storage Cold Disk Tape Cloud 4

Scalability without compromise Capacity, Performance & Reliability Scale Here Lustre* Clients Lustre* Clients Lustre* Clients Lustre* Filesystem Front-End I/O Lustre* OSS/OST Building Block Lustre* OSS/OST Building Block Lustre* Lustre* OSS/OST Lustre* OSS/OST OSS/OST Building Building Building Block Block Block Lustre* Lustre* MDS/MDT Lustre* MDS/MDT MDS/MDT Building Building Block Building Block Block Scale Here More File Systems DMF Managed HSM Environment DMF Direct Archiving Back-End I/O TAPE Parallel DMF Data Mover Building Block JBFS TAPE JBFS Parallel DMF Data Mover Building Block TAPE TAPE TAPE JBFS JBFS JBFS Parallel Parallel Parallel DMF DMF Data DMF Data Mover Data Mover Mover Building Building Building Block Block Block SSD SSD DMF MDS Scale Here 2015 5 SGI 2014 SGI * = Some names and brands may be claimed as the property of others 5

UV 300 & Flash: Converged Compute & Storage Platform Single scale-up SMP system delivers Compute: Up to 480 Intel Xeon cores (32 sockets) Memory: Up to 24TB DRAM Non-volatile Memory: Up to 128TB FLASH Up to 30 Million IOPs Up to 200GB/s All in one rack No switches, no arrays, no problems Intel P3700 400K IOPS 2.4GB/s 7

Optimized Code Examples Direct, parallel I/O Leveraging multi-queue capability of NVMe Deploys asynchronous I/O & threads Moving data in parallel on multiple sockets uvcp Replaces standard cp command Up to 50x improvement 25 GB/s copy with 32 NVMe cards 50GB/s combined uvmem Quick loading of files into memory 35-40 GB/s with 32 NVMe cards 9

Lustre Storage Environment NFS Storage Interface UV Flash Storage Data Output Direct to UV Flash UV HPDA Application SGI VIzServer Customer Deployment Example HPC Cluster Node SGI UV HPC Cluster Node HPC Cluster Node Remote Users HPC Cluster Node Data Analytics Workflow Pipeline 10

UV Tiered Data Concept User Application I/O 100ns-1us latency Memory File System Persistence and capacity management Scalable UV node 10ms latency 100us latency Internal Flash DMF SGI Flash capacity management Complete Infrastructure 11 11

UV Tiered Data Components Phase 1 Phase 2 Compute: 32 Sockets Intel Xeon Memory: 24TB DRAM Non-volatile Memory: 128TB Flash NVMe 30 Million IOPS 200 GB/s UV300 with PCIe Flash High performance at 1/5 array cost Transparent Data Extension: Great performance and cost Leverages DMF Software: Hybrid solution Cold Storage on Disk Infinite capacity at cost of media 12

UV Tiered Data Solutions Data intensive HPC/HPDA applications running on UV High-performance Lustre OSS/OST with DMF for Lustre servicing compute cluster Alternative fabric / namespace server, such as NFS over RDMA Distributed databases such as Apache Spark running on UV Application virtualization on UV (OpenStack, VDI) HPC customers increasingly request OpenStack Databases (PostgreSQL) on UV 13

Data Management for HPC Future Direction 14

Performance Standard XFS 3M read IOPS max App App App XFS Filesystem Linux md RAID-0 Single queue bottleneck, 3M IOPS max NVM NVM NVM NVM NVM NVM NVM NVM 16

SGI s Enhanced XFS 13M read IOPS (32 cards) App App App XFS Filesystem Linux md RAID-0 Direct parallel access to NVMe queues NVM NVM NVM NVM NVM NVM NVM NVM Demonstrated at ISC 15 17

HA System Concept Primary10GbE 10GbE NL7 PCIe 3.0 PCIe 3.0 10GbE NL7 10GbE Primary system 10GbE Secondary system Secondary10GbE 18

Data Tiering with DMF Today Code (POSIX) Parallel Filesystem (Lustre) Archive (Tape, JBFS) Codes require POSIX Buffered or Direct I/O MPI communications High streaming performance Limited namespace (1B) Redundancy required Good streaming performance Limited namespace (1B) Mirroring only No multisite support No replication to cloud Manual archive replication only 19

Dynamic Namespaces What if we could construct namespaces (i.e. filesystems) on the fly and present them to codes? Initially all files are offline. We use DMFlike recall triggered by scheduler to bring data into target tier (e.g. Flash) Then we run HPC job Scheduler triggers migration, then backs up namespace 20

Data Tiering for HPDA Code (POSIX) Filesystem Cache (Burst Buffer) Parallel Filesystem (Lustre) Archive (Object store) Codes require POSIX Buffered or Direct I/O MPI communications Highest random I/O performance Limited namespace (up to 100M) Flexible or no data redundancy High streaming performance Medium namespace (1B) Redundancy required Good streaming performance Very large namespace (over 10B) Erasure codes and DR 21

Future Data Tiering for HPDA Code (POSIX) Filesystem Cache (Burst Buffer) Archive (Object store) Codes require POSIX Buffered or Direct I/O MPI communications Highest random I/O performance Limited namespace (up to 100M) Flexible or no data redundancy Good streaming performance Very large namespace (over 10B) Erasure codes and DR Third-party archive integration Geographic replication & Backup For example, using DDN WOS 22

Summary and Discussion Kirill Malkin kmalkin@sgi.com 23