I will be giving a talk about performance characterization and tuning of Scylla on Samsung NVMe SSDs. We will characterize the performance of Scylla on Samsung high-performance NVMe SSDs and show how Z-SSD ─ the Samsung ultra-low-latency NVMe drive ─ can significantly shrink the performance gap between in-memory and in-storage with Scylla. We will further evaluate the throughput-vs-latency profile of Scylla with NVMe devices and present end-to-end latencies (from the client's viewpoint) as well as the latencies of the software/hardware stack. We will show that a Z-SSD-backed Scylla cluster can provide competitive performance to an in-memory deployment while sharply reducing costs.

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Scylla on Samsung Z-SSD
Senior Performance Architect, Samsung Semiconductor Inc.
Arash Rezaei

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Arash Rezaei
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Arash is a senior performance architect at Samsung
Semiconductor Inc. His work has been primarily on
performance evaluation and tuning of data center
applications with a focus on storage.

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Agenda
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▪ Z-SSD – Samsung’s ultra-low latency SSD
▪ Z-SSD use-cases
▪ Scylla on Z-SSD
▪ Summary

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Introduction: Latency Matters
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▪ Threshold of patience is decreasing
o Retrieving data from caches, databases, data stores
o Business analytics
MySQL/ NoSQL
Databases
Streaming
Data
Storage
Layer
Cache Layer
Web
Layer
Analytics
Latency

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Samsung Z-SSD
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▪ Ultra-low latency flash storage device
▪ Provides 5.5x lower latency comparing to today’s leading NVMe SSD
14.7
80.3
0 10 20 30 40 50 60 70 80 90
Z-SSD
PM1725a
Latency [usec]
4K Random
Read Latency
5.5x Lower Latency
fio --rw=randread --bs=4k --direct=1 --iodepth=1 –numjobs=1 --
ioengine=libaio --norandommap

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Samsung Z-SSD
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DRAM
Z-NAND
New Controller
50%▼
Past LP4
70%▼
New CTRLPast
x 1/10 ▼
Z-NANDPast
▪ Samsung’s Z-SSD is vertically optimized from DRAM to storage

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SZ985: Samsung Z-SSD
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▪ Sequential traffic
o 3.2 GB/sec Read
o 3.2 GB/sec Write
▪ Random traffic
o 750K IOPs Reads
o 170K IOPs Writes
▪ Capacity
o 800GB

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Z-SSD Minimizes Latency
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▪ High performance @ consistent low latency
SSD
Throughput Latency
Sequential
R/W
Random
R/W
Random
Read
PM1725a
3.3/2.95
GB/s
800/160
KIOPS
90µs
Z-SSD 3.2/3.2 GB/s
750/170
KIOPs
15µs
Read-only workload (FIO) Mixed (80%/20% R/W) FIO

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Z-SSD Use Cases

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Z-SSD Benefits Latency-Sensitive Apps (1/2)
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▪ Z-SSD as swap space
▪ Memcached: distributed
object caching system
▪ 3x speedup @ 1
3 the
average latency under
heavy swap load
0
20000
40000
60000
80000
100000
memcached
Throughput[op/sec]
Memcached
Throughput
PM1725a Z-SSD
0
200
400
600
800
1000
1200
1400
memcached
ReadLatency[usec]
Memcached
Latency
PM1725a Z-SSD
3x
𝟏
𝟑
memcached with 60GB dataset (45 million records, value size=1000B)
DRAM capacity=32GB (less than half of the used memory space)
Driven with YCSB, 90% read/ 10% update

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Z-SSD Benefits Latency-Sensitive Apps (2/2)
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▪ Z-SSD as storage layer
▪ RocksDB is used as storage
engine for DBs
▪ 2x throughput @ ½ the
average latency
0
20000
40000
60000
80000
100000
120000
140000
RocksDB
Throughput[op/sec]
RocksDB
Throughput
PM1725a Z-SSD
2x
0
50
100
150
200
250
300
350
RocksDB
AverateLatency[usec]
RocksDB
Average Latency
PM1725a Z-SSD
½
db_bench read-while-writing workload

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Scylla on Z-SSD

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Methodology
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▪ Goal:
o Compare Scylla in-memory vs. Scylla on Z-SSD
▪ Metric:
o Max throughput under given tail-latency constraints
▪ Workload:
o Cassandra-stress with:
• Varying Read/Write ratio (100%/0% – 75/25% )
• Varying % of request served from memory (25% to 75%)
o Database populated with 300GB data (payload 1KB)

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System Configuration
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Item Description
CPU 2 x Intel Xeon Gold 6154 @
3.00GHz (total 36 cores per node)
RAM 128GB
SSD 2 x SZ985 800GB
OS Ubuntu 16.04.2, Kernel 4.12.0
Scylla version 2.0

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Throughput while Meeting Latency SLA (1/2)
▪ 100% read workload
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Sub millisecond 95 percentile latency Sub 2 millisecond 99 percentile latency

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Throughput while Meeting Latency SLA (1/2)
▪ 100% read workload
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Sub millisecond 95 percentile latency Sub 2 millisecond 99 percentile latency

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Throughput while Meeting Latency SLA (2/2)
▪ 75% read/25% write workload
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Sub millisecond 95 percentile latency Sub 2 millisecond 99 percentile latency

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Throughput while Meeting Latency SLA (2/2)
▪ 75% read/25% write workload
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Sub millisecond 95 percentile latency Sub 2 millisecond 99 percentile latency

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▪ Server viewpoint
▪ Latency under a fixed throughput
▪ 100% read workload
(95 percentile latency)
Software Overheads

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▪ Server viewpoint
▪ Latency under a fixed throughput
▪ 100% read workload
(95 percentile latency)
Software Overheads
Device tail latency from FIO experiments

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Scylla: DRAM, Z-SSD, or NVMe SSD?
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▪ For a given use-case requirement (throughput and DB size), what is
the most cost-efficient cluster configuration?
▪ Optimize performance/$ for different use-cases

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Summary
▪ Samsung Z-SSD: ultra-low latency SSD device
o 5.5x lower latency compared to NVMe SSD
▪ Z-SSD benefits latency-sensitive applications
o RocksDB: 2x throughput @ ½ the average latency
o Memcached (as swap): 3x speedup @ 1
3 the average latency
▪ Z-SSD for Scylla:
o Helps reduce the performance gap between memory and storage
• Delivers 44% – 23% of DRAM performance at significant lower cost
– 50% – 75% of requests served from memory
o Software improvements could further shrink the memory/storage gap
o Opens new options for architecting a large cluster
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THANK YOU
a.rezaei@samsung.com
Please stay in touch
Any questions?