x86-less ScyllaDB: Exploring an All-ARM Cluster
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Mike Bennett from Ampere and Keith McKay from ScaleFlux presented on exploring an all-ARM ScyllaDB cluster without x86 processors. They discussed the cluster configuration using Ampere Altra Max ARM servers with ScaleFlux SSDs. Benchmark results showed sub-millisecond latency for 100% reads and over 1 million operations per second for mixed workloads. They called for interested parties to contact Ampere and ScaleFlux for access to hardware and storage to further explore the benefits of high performance and efficiency of all-ARM clusters.
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x86-less ScyllaDB: Exploring an All-ARM Cluster
- 1. x86-less ScyllaDB: Exploring an All-Arm Cluster Mike Bennett, Ampere Keith McKay, ScaleFlux
- 2. Mike Bennett ■ Solution Architect ■ 18 years experience in IT, 9 in solution development ■ Enjoys servers with many cores ■ Reverse migrated from Texas to California in 2022
- 3. Keith McKay ■ Responsible for applications engineering at ScaleFlux ■ Loves non-volatile memory and storage ■ Born in Mountain View, CA (long before Google).
- 4. ■ Cluster Configuration ■ Introduction to Ampere & ScaleFlux ■ Benchmark Setup & Results ■ Call to Action Agenda
- 6. A ScyllaDB Cluster Without x86 8x Embedded ARM Cores Per SSD 128x Arm Cores Per node 256GB DDR4-3200 Mt. Collins Single Socket NICs: Mellanox ConnectX-6 Client Client Client CSD-3000 Series NVMe (PCIe Gen4 x4) ZERO data processed, moved, or stored using x86 instructions x4 x4 x4 SUSE Linux Enterprise Server 15 SP4 (kernel 5.14.21-150400.24.38-default) | 256GiB DRAM | Ampere Altra Max @ 3.0GHz ScyllaDB Enterprise: 2022.1.3-0.20220922.539a55e35 | 100Gb Ethernet
- 7. Why Is This Important? ■ Low Power ■ High CPU Density ■ High Performance Higher Efficiency → Lower TCO
- 8. Introduction to Ampere Computing® & ScaleFlux®
- 9. Ampere® Altra® is the World’s First Cloud-Native Processor Ampere® Altra® Max Ampere® Altra® 7nm 80 Cores 7nm 128 Cores Predictable High Performance Elastic and Scalable Power Efficient and Sustainable Larger Low Latency Private Caches Single-Threaded Cloud Core Consistent Operating Frequency Maximum Core Counts Power and Area-Efficient Smaller Private Caches Multi-Threaded Client Core Inconsistent Operating Frequency Limited Core Counts Power and Area-Inefficient Legacy Architectures Ampere Architecture Arm Native Cloud Native Video Services Web Services Data Services AI
- 10. ScaleFlux: A Better SSD Datacenter Class NVMe SSD Compute Engines ● U.2 and E1.S Form Factors ● 3.84TB to 16TB+ capacity ● Enterprise feature set ○ TCG Opal, SR-IOV, etc. Compute Capabilities: ● Transparent compression ● Data filtering ● Security acceleration
- 12. Test Scenarios cassandra-stress write no-warmup n=1342177280 cl=local_quorum -schema "replication(factor=3)" -mode native cql3 -pop seq=1.. 10214748364 -col size=gaussian(214..748,364.80) … ~6x Updates ~1TB Shard-aware driver Incremental Compaction (Default for Enterprise) Varied column data size Scenario 1: 100% Read with Gaussian Distribution Scenario 2: 75% Read / 25% Write with Gaussian Distribution Scenario 3: 50% Read / 50% Write, Dataset in Memory Load Phase:
- 13. Cluster Limits: 100% Read 100% Read over 10B Records Gaussian Access Pattern cassandra-stress read n=1000000000 cl=ONE -pop dist=GAUSSIAN(1.. 10214748364) -schema keyspace="keyspace1" -mode native cql3 … Sub-millisecond P99 @ 1.4 Mops/sec
- 14. Cluster Limits: 75/25 Mixed R/W 75/25 Read-Write over 10B Records Gaussian Access Pattern cassandra-stress mixed ratio(write=1,read=3) n=1000000000 cl=ONE -pop dist=GAUSSIAN(1.. 10214748364) -schema keyspace="keyspace1" -mode native cql3 … 1.1 Mops/sec with ~100 running compactions
- 15. Cluster Limits: 50/50 Read/Write 50/50 Read-Write over 1M Records cassandra-stress mixed ratio(write=1,read=1) n=1000000000 cl=ONE -pop dist=UNIFORM(1..1000000) -schema keyspace="keyspace1" -mode native cql3 … 1.4 Mops/sec with a uniform distribution.
- 16. Call to Action
- 17. Why Is This Important? ■ Low Power ■ Benchmarks used under 4W per CPU core (410 - 490W per server) ■ Rack Math ■ Including platform, memory, network IO, and storage IO power ■ High CPU Density ■ Fewer database nodes required, lower CapEx & OpEx ■ Ideally suited to ScyllaDB shard-per-core architecture ■ High Performance ■ Better performance & economics compared to cloud deployments ■ Unmatched ops/sec and latency performance
- 18. Ampere Developer Access Program ■ Get access to hardware ■ Remote access to bare metal servers ■ Trial systems shipped to you ■ Partner cloud programs ■ Solution architects available to help you get up and running! https://solutions.amperecomputing.com/where-to-try
- 19. ScaleFlux PoC Program ■ Request sample units at info@scaleflux.com ■ Be sure to mention that you saw us at the ScyllaDB Summit! ■ Learn more about ScaleFlux and “A Better SSD” at our website ■ https://www.scaleflux.com ■ Feel free to reach out to me directly using the contacts at the end of this presentation (fair warning: I love talking about storage!)
- 20. Thank You Stay in Touch Mike Bennett mbennett@amperecomputing.com https://github.com/mikebatwork https://www.linkedin.com/in/mbamike1/ Keith McKay keith.mckay@scaleflux.com @keefmck https://github.com/kpmckay www.linkedin.com/in/kpmckay