Panel Discussion: Is Computational Storage a Better Path to Extreme Performance?

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Vendors are re-writing software and adding custom hardware in an attempt to not bottleneck extremely low latency NVMe Flash and Storage Class Memory technologies. Eventually, they all are at the mercy of physics. Data has to traverse an internal and sometimes and external network so the computing tier can process it. Computational Storage offers an alternative by performing at least some of the processing on the storage device itself, eliminating most of the network activity. Join Storage Switzerland's Lead Analyst, George Crump as he leads a panel of computational storage experts to include NGD System's Scott Shadley, ScaleFlux's Thad Omura, and Samsung's Pankaj Mehra as preview the Computational Storage Workshop at the Flash Memory Summit on Thursday, August 8th.

Technology

Will Your Backup
Architecture Meet
Tomorrow’s SLAs?
3 Steps to Make Sure!
For audio playback and Q&A go to:
bit.ly/ExtremePerform

George Crump,
Lead Analyst & Founder
Thad Omura,
EVP Marketing &
Operations
Scott Shadley,
VP of Marketing
Pankaj Mehra,
VP, Product
Planning Team
Nick Adams,
Board Member

what are some USE
CASES & SUCCESS
STORIES?

Presented by Scott Shadley, VP of Marketing
ngdsystems.com info@ngdsystems.com @NGDsystems

Form Factor
Available
In 2019
Capacity
(TB)
MAX Power
(W)
M.2 22110 NOW up to 8 8
EDSFF E1.S Q3 up to 16 12
EDSFF E1.L Q3 Up to 32 12
U.2 15mm NOW up to 32 12
AiC FHTQL up to 64 15
NGD Systems Computational Storage Solutions
June 11, 2019 NGD Systems, Inc. – Webinar 7
>10x faster Image
Classification
40% faster
1/3 the Space
Lower TCO
Native, Real-Time
Applications
500x Faster
Image Matching
OS running
On Drive

Presented by Thad Omura, EVP Marketing & Operations
scaleflux.com info@scaleflux.com /scaleflux

9Proprietary & Confidential
 Up to 8TB capacity
• Multi-NAND vendor
3D TLC
 GZIP, EC HW Engines
 Atomic Writes,
Namespace Streams
 Tunable latency &
performance
ScaleFlux Computational Storage
200%
Latency Consistency
Host FM & Tunable Performance
Customer Specific Workload
CSD vs. NVMe
200%
Queries Per Second
Atomic Write Support
Sysbench OLTP write-only
CSD vs. NVMe
161%
Jobs Completed
GZIP & EC Compute Engines
Teragen, Terasort
CSD+HDD vs. HDD only
3.0
*Applies to HDFS &
Up to 500%
GZIP Write Throughput
GZIP Compute Engines
FIO
CSD GZIP vs. CPU GZIP
260%
GZIP Write Throughput
GZIP Compute Engines
YCSB Load Benchmark
CSD vs. NVMe

Presented by Pankaj Mehra, VP - Product Planning Team
samsung.com /SamsungUS @SamsungUS

11 / 7C O L L A B O R A T E . I N N O V A T E . G R O W .
Samsung SmartSSD Technology Roadmap
Roadmap to smaller FF (U.2) and greater integration with SSD controller
Moves Data out ofSSDvia CPU &Memory
Limited scalability: Funnels 3 SSDs 1 FPGA
SmartSSD PoC
InternalDataTransfer
AddsBandwidthandProcessing
withoutFunneling
U.2 V1.0 SmartSSD
External FPGA
‘Q4’2018
HHHL AIC PoC
2H’2020 ~ 1H
2021
2nd Generation
2H’2019
U.2 MP
U.2FF:ScaleProcessingto24or48devices
2/4/8TB,25W,PCIeGen3x4,~300KLUTs
for accelerationkernels
NextGenSmartSSD
GreaterIntegrationand
MoreInternalBandwidth

12 / 7C O L L A B O R A T E . I N N O V A T E . G R O W .
Pushing Intelligence to Data
CPU
CPU
FPGA
/ GPU
PCIe
Today’s Architecture
Heavy domain-specific
compute in CPU
SSD
Large amount of
data transferred
SSD
SSD
TBs, PBs, EBs
dataset
PCIe
Storage and Data Acceleration
High, scalable
total internal BW
SSD
CTRL
FPGA
Accelerator
Offload,
UDF Accel.
&
Near-Data
Processing
Performance
# SmartSSD / serverNAND
Scale Performance with Data
 Concurrent processing on large amount of data
 Offloaded processing near the data
 HW acceleration of certain domain-specific fns.
 Immediate Insight from Data
Performance Ceiling
 Bottlenecks: Root complex, Ext FPGA
 Unnecessary data movement
 IO BW pressure on Host CPU, DRAM
SmartSSD
Performance
# SSDs / server
Today
CPU
Performance Ceiling
2x to 10x
DRAM
DRAM
$
CPU
CPU
DRAM
DRAM
$

Presented by Nick Adams, Board Member
snia.org /SNIA.ORG @SNIA

CONTACT US
Storageswiss.com
georgeacrump@storageswiss.com
@storageswiss
storageswiss

Will Your Backup
Architecture Meet
Tomorrow’s SLAs?
3 Steps to Make Sure!
For complete audio and Q&A please register for the
On Demand Version: bit.ly/ExtremePerform

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In this session, we will discuss the journey of API governance from its initial, ungoverned state to the development of sophisticated models that tackle contemporary challenges. We'll explore how APIs have become essential in the intersection of business and technology, adapting to advancements and evolving needs. We'll focus on how organizations have moved from launching to monetizing APIs, using models like pay-per-use and subscriptions, and finding the right balance between technical implementation and business strategy. We'll also highlight the impact of governance on monetization strategies, especially how data security, compliance, and service quality influence pricing. Real-world examples will demonstrate the effective integration of governance with monetization, including AI's role in dynamic pricing. Looking ahead, we'll share insights into future trends in API governance and monetization, emphasizing the importance of adaptability, continuous learning, and innovation.

API Governance and Monetization - The evolution of API governance

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Key topics covered: - Understanding the basics of IAM and its significance in the modern enterprise. IAM in a platformless environment - Tackling real-world issues like prioritizing frictionless yet secure user access, securing high-value APIs, integrating to business, compliance, and adapting to cloud native environments with scalable solutions - Practical demonstrations of how WSO2 products can be instrumental in deploying efficient IAM solutions - Preparing for upcoming trends and innovations in identity management

Navigating Identity and Access Management in the Modern Enterprise

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Choreo: Empowering the Future of Enterprise Software Engineering

API Governance and Monetization - The evolution of API governance

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Panel Discussion: Is Computational Storage a Better Path to Extreme Performance?

1. Will Your Backup Architecture Meet Tomorrow’s SLAs? 3 Steps to Make Sure! For audio playback and Q&A go to: bit.ly/ExtremePerform

2. George Crump, Lead Analyst & Founder Thad Omura, EVP Marketing & Operations Scott Shadley, VP of Marketing Pankaj Mehra, VP, Product Planning Team Nick Adams, Board Member

3. what is COMPUTATIONAL STORAGE?

4. why does it MATTER?

5. what are some USE CASES & SUCCESS STORIES?

6. Presented by Scott Shadley, VP of Marketing ngdsystems.com info@ngdsystems.com @NGDsystems

7. Form Factor Available In 2019 Capacity (TB) MAX Power (W) M.2 22110 NOW up to 8 8 EDSFF E1.S Q3 up to 16 12 EDSFF E1.L Q3 Up to 32 12 U.2 15mm NOW up to 32 12 AiC FHTQL up to 64 15 NGD Systems Computational Storage Solutions June 11, 2019 NGD Systems, Inc. – Webinar 7 >10x faster Image Classification 40% faster 1/3 the Space Lower TCO Native, Real-Time Applications 500x Faster Image Matching OS running On Drive

8. Presented by Thad Omura, EVP Marketing & Operations scaleflux.com info@scaleflux.com /scaleflux

9. 9Proprietary & Confidential  Up to 8TB capacity • Multi-NAND vendor 3D TLC  GZIP, EC HW Engines  Atomic Writes, Namespace Streams  Tunable latency & performance ScaleFlux Computational Storage 200% Latency Consistency Host FM & Tunable Performance Customer Specific Workload CSD vs. NVMe 200% Queries Per Second Atomic Write Support Sysbench OLTP write-only CSD vs. NVMe 161% Jobs Completed GZIP & EC Compute Engines Teragen, Terasort CSD+HDD vs. HDD only 3.0 *Applies to HDFS & Up to 500% GZIP Write Throughput GZIP Compute Engines FIO CSD GZIP vs. CPU GZIP 260% GZIP Write Throughput GZIP Compute Engines YCSB Load Benchmark CSD vs. NVMe

10. Presented by Pankaj Mehra, VP - Product Planning Team samsung.com /SamsungUS @SamsungUS

11. 11 / 7C O L L A B O R A T E . I N N O V A T E . G R O W . Samsung SmartSSD Technology Roadmap Roadmap to smaller FF (U.2) and greater integration with SSD controller Moves Data out ofSSDvia CPU &Memory Limited scalability: Funnels 3 SSDs 1 FPGA SmartSSD PoC InternalDataTransfer AddsBandwidthandProcessing withoutFunneling U.2 V1.0 SmartSSD External FPGA ‘Q4’2018 HHHL AIC PoC 2H’2020 ~ 1H 2021 2nd Generation 2H’2019 U.2 MP U.2FF:ScaleProcessingto24or48devices 2/4/8TB,25W,PCIeGen3x4,~300KLUTs for accelerationkernels NextGenSmartSSD GreaterIntegrationand MoreInternalBandwidth

12. 12 / 7C O L L A B O R A T E . I N N O V A T E . G R O W . Pushing Intelligence to Data CPU CPU FPGA / GPU PCIe Today’s Architecture Heavy domain-specific compute in CPU SSD Large amount of data transferred SSD SSD TBs, PBs, EBs dataset PCIe Storage and Data Acceleration High, scalable total internal BW SSD CTRL FPGA Accelerator Offload, UDF Accel. & Near-Data Processing Performance # SmartSSD / serverNAND Scale Performance with Data  Concurrent processing on large amount of data  Offloaded processing near the data  HW acceleration of certain domain-specific fns.  Immediate Insight from Data Performance Ceiling  Bottlenecks: Root complex, Ext FPGA  Unnecessary data movement  IO BW pressure on Host CPU, DRAM SmartSSD Performance # SSDs / server Today CPU Performance Ceiling 2x to 10x DRAM DRAM $ CPU CPU DRAM DRAM $

13. 13 / 7C O L L A B O R A T E . I N N O V A T E . G R O W . TPC-DS Spark Q73 (Nested scan) • Before: • After: Samsung SmartSSD Illustrative Performance Profile

14. Presented by Nick Adams, Board Member snia.org /SNIA.ORG @SNIA

15. CONTACT US Storageswiss.com georgeacrump@storageswiss.com @storageswiss storageswiss

16. Will Your Backup Architecture Meet Tomorrow’s SLAs? 3 Steps to Make Sure! For complete audio and Q&A please register for the On Demand Version: bit.ly/ExtremePerform

Panel Discussion: Is Computational Storage a Better Path to Extreme Performance?

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