Trish DamkrogerVice President, Data Center GroupGeneral Manager, Technical Computing Initiative

Before We Begin - The coming flood of dataBy 2020…

The average internet user will generate

~1.5 GB of traffic per daySmart hospitals will be generating over

3,000 GB per day

A connected plane will be generating over

40,000 GB per dayA connected factory will be generating over

1,000,000 GB per day

Self driving cars will be generating over

4,000 GB Per day … Each

The world is changing – without Analytics and aI workloads we will drown in data!!!

Different Systems (Today)

FORTRAN / C++ ApplicationsMPI

High Performance

Java* ApplicationsHadoop*

Simple to Use

SLURMSupports large scale startup

YARN*More resilient of hardware failures

Lustre*Remote Storage

HDFS*, SPARK*Local Storage

Compute & Memory FocusedHigh Performance Components

Storage FocusedStandard Server Components

Server StorageSSDs

SwitchFabric

Infrastructure

ProgrammingModel

Resource Manager

File System

Hardware

Server StorageHDDs

SwitchEthernet

Infrastructure

3Daniel Reed and Jack Dongarra, Exascale Computing and Big Data in Communications of the ACM journal, July 2015 (Vol 58, No.7), and Intel analysisOther brands and names are the property of their respective owners.

Emerging Real-Time Workflows

Small Data + Small Compute

e.g. EDA

Big Data + Small Compute e.g. Search, Streaming, Data Preconditioning

Small Data +Big Compute

e.g. Mechanical Design, Multi-physics

Da

ta

Compute

4

One System Architecture?

From Here … …TO?

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The Challenges of Moving to (HPC && Big Data)

Source: NERSC Workload Analysis on Hopper. K. Antypas et al. 2014

Many Codes on a System

Over 600 Different Applications on NERSC’s Hopper System

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The Challenges of Moving to (HPC && Big Data)

Source: NERSC Workload Analysis on Hopper. K. Antypas et al. 2014

Many Codes on a System

Over 600 Different Applications on NERSC’s Hopper System

Source: Intel for illustration purposes

Varied Resource Needs

Typical HPC Workloads

High Frequency

Trading

Numeric Weather

Simulation

Oil & Gas Seismic

Sy

ste

m c

ost

ba

lan

ce

Typical Big Data Workloads

Video Survey Traffic Monitor

Personal Digital Health

Sy

ste

m c

ost

ba

lan

ce

Processor Memory Interconnect Storage

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Benefits of a Single System Architecture

Flexibility to manage workflows and maximize system utilization

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Improved Total Cost of Ownership

Overcomes cost and complexity of moving data

Potential for a unified SW ecosystem

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Realizing the Benefits Requires Coordinated Design

ComputeMany core

Multicore

Intel Graphics

Intel Xeon + FPGA

System Software StackSimplifies Use and Application Development

InterconnectConfigurable

Next-Generation Fabric

Memory/StorageConfigurable High BW Memory

Non-Volatile MemoryStorage Burst BufferLustre File System

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Converged Architecture for HPC and Big Data

10

FORTRAN / C++ ApplicationsMPI

High Performance

Java* ApplicationsHadoop*

Simple to Use

Lustre* with Hadoop* AdapterRemote Storage

Compute & Big Data CapableScalable Performance Components

Server Storage(SSDs and Burst Buffers)

Intel®Omni-Path

Architecture

Infrastructure

Programming Model

Resource Manager

File System

Hardware

*Other names and brands may be claimed as the property of others

HPC & Big Data-Aware Resource Manager

Key Enabler: A Configurable Memory-Storage Hierarchy

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Processor

Compute Node

I/O Node

Remote Storage

Compute

Today

Caches

Local Memory

SSD Storage

Parallel File System(Hard Drive Storage)

Hig

he

r B

an

dw

idth

. L

ow

er

La

ten

cy a

nd

Ca

pa

city

Some remote data moves onto I/O node

I/O Node storage moves to compute node

Local memory is now faster & in processor package

Compute

Future

Caches

Non-Volatile Memory

Burst Buffer Storage

Parallel File System (Hard Drive Storage)

In-Package High Bandwidth Memory*

*cache, memory or hybrid mode

MachineLearning

Modeling & Simulation

High PerformanceData Analytics

Many workloads | One architectural framework

Small Clusters Through Supercomputers

Standards-Based Programmability

On-Premise and Cloud-Based

Intel® Scalable System Framework

Compute and Data-Centric

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