Revolutionizing the Datacenter

Join the Conversation #OpenPOWERSummit

A Year of Growth in CAPI Solutions

Bruce Wile, CAPI Chief Engineer

IBM

Join the Conversation #OpenPOWERSummit

Join the Conversation #OpenPOWERSummit

� Feb 2015

• 2 Accelerators:

� IBM Data Engine for NoSQL

� Algo-Logic L3 Order Book

• Key Message to CAPI Team:

“Go make more accelerators”

• 1 Developer Kit Card

(Nallatech)

� Feb 2016

• Dozens of accelerators

• 3 Developer Kit Companies

(Nallatech, Alpha-Data,

Semptian)

� Each with new cards in the

works

One year later…..Feb 2015 vs. Feb 2016

2

Join the Conversation #OpenPOWERSummit

CAPI Acceleration Types

3

Accelerator

on FPGA

Accelerator Library

ApplicationApplication

ApplicationApplication

Accelerator Building Block

Function API

SAN48-16G

1 U

2 U

3 U

4 U

5 U

6 U

7 U

8 U

9 U

10U

11U

12U

13U

14U

15U

16U

17U

18U

19U

20U

21U

22U

23U

24U

25U

26U

27U

28U

29U

30U

31U

32U

33U

34U

35U

36U

37U

38U

39U

40U

41U

42U

~AC ~AC1 G G8264

121

1-2

840

Power S822LC146GB 15K SAS146GB 15K SAS

Power S822LC146GB 15K SAS

146GB 15K SAS

Power S822LC146GB 15K SAS

146GB 15K SAS

Power S822LC146GB 15K SAS

146GB 15K SAS

Power S822LC146GB 15K SAS

146GB 15K SAS

Power S822LC146GB 15K SAS

146GB 15K SAS

Power S822LC146GB 15K SAS

146GB 15K SAS

146GB 15K SAS

146GB 15K SAS

Application + AcceleratorFull Solution

External IO(available)

Accelerator Types:

Transparent: API is pre-

existing/common such that the

application does not need to change to

take advantage of acceleration.

Integration Required: Application

developer must write code to utilize the

accelerator

Full Solution: Application and

accelerator are part of a complete

solution sold to end customers.

Join the Conversation #OpenPOWERSummit

Catalog of CAPI Accelerators – By Type

4/1/2016 4

Transparent

Erasure Code

GZIP Compression

PairHMM Accelerator

LA Library

Bitwise Encryption

Full Solution

Genomics Processing

Graph Analytics Djikstra

Novara-Fuzzy Text Search

Petascale Indexing

Integration Required

IBM Data Engine for No-SQL

(“CAPI-Flash”)

Fast-Fourier Transfer

Monte Carlo Risk Analysis

CV Library

DNN Library

Key Value Store (KVS)

Dynamic Time Warp Pattern

Match

L3 Order Book

Mood Detection

Object Detection

Object Recognition

Object TrackingWith many more coming…..

Join the Conversation #OpenPOWERSummit

CAPI Development Ecosystem

4/1/2016 5

CAPI Developer Kits available from…. CAPI Frameworks, Examples …..

P8 AFU

DMA Mover

CAPI Framework

Memcopy Example

PSL +

DMA

AFUP8 +

PSL

PSL Sim Engine

AFU

AccDNN-Caffe to CAPI

Join the Conversation #OpenPOWERSummit

IO

Card

6

Database Analytics: Four Paradigms for Comparison

SW Threads

Data

DB2

MEMORY

Analytics

SW Only

Data PathKEY:

HW

Algorithm

Processor Chip

AIO

CardData

DB2

MEMORYFPGA

Analytics

Dev Driver

DD Mem

PCI-E FPGA Acceleration+ Accelerated Analytics on FPGA gains performance for many algorithms

- Device driver overhead and programming difficulty

Processor Chip

B

IO

CardData

DB2

FPGA

Analytics

CAPI FPGA Acceleration

MEMORY

POWER8 Chip

+ Accelerated Analytic on FPGA gains performance for many algorithms

+ Shared Memory model for ease of programming and fast access

+ Performance gains through pipelining of analyzed data (vs. large block

release)

+ Frees processor threads for other work

CA

PI

C

Data

DB2

FPGA

Analytics

CAPI FPGA Acceleration with

Database Integration (Data in Motion)

MEMORY

POWER8 Chip

+ All advantages of CAPI FPGA Acceleration

+ Single data flow into processor IO yields much higher performance

D

CA

PI

Join the Conversation #OpenPOWERSummit

Workload Acceleration of Informix

4/1/2016 7

� Description: This is a project to prove the Value of Power 8 for typical IoT Workload

Acceleration, exemplified by Dynamic Time Warping: a subsequence similarity measurement

algorithm accelerated with FPGA

� Client Value: Faster subsequence similarity search over the historical IoT data than CPU based

computing, balanced in-database analysis(without moving data to a separate analytics

platform) even under consistent data ingestion.

Example: I want to know the times motif like “A” appeared in the history.

AAAA

Join the Conversation #OpenPOWERSummit

Emotion Detection for Retail Analytics

CAPI Bridge

Expression Recognition

Gender

Classify

Face

Detect

Age

Classify

Vision Accelerator Interconnect

Vision Accelerator PlatformOpportunity – Gain valuable shopper

insights by inferring shopper demographic

and behavior patterns from many

strategically placed cameras.

Product

Detection

Gender: Male

Age: 20 – 30

Gaze: 5 seconds

Impression: positive