8 dome results · dome project: dome research streams… 1. algorithms & machines 2. access...

DOME

DOME: Results.

www.dome-exascale.nl

Prof. Dr. Ton Engbersen,IBM Research Laboratory – Zurich, SwitzerlandScientific Director ASTRON-IBM Center for Exascale Technology, NetherlandsProf. Data Science Engineering, Rijksuniversiteit Groningen, NetherlandsMember IBM Academy of Technology

DOMEDOME: What is it?

IBM-NL

IBM-ZRLASTRON

€ €

€ €

DOME

DOME: Why?

3

Platformen

Photonics

Modelling

Algorithms

Storage solutions

Access patterns

Dome Project:

SystemAnalysis

Data&StreamingSustainable(Green)Computing Nanophotonics

Computing Transport Storage

Modelling

- Nanophotonics- Real-TimeCommunications- NewAlgorithms

- Microservers- Accelerators

- AccessPatterns

ResearchStreams…

…aremappedtoresearchprojects:

…plusanopenuserplatform:Userplatform

- Studentprojects- Events- ResearchCollaboration

5-year Research Project: 76 IBM PY (32 in NL); 50 ASTRON PY

Impact of DOME on SKA:

DOME Symposium 18-19 Mei 2017

5

SCIENCE REGIONAL CENTRE

SRC

MicroserversPhotonics

AcceleratorsAlgorithms

Data access patterns

Modeling

Real time communications



6


SRC




Modeling


Dome Project: DOME

ResearchStreams…

1. Algorithms&Machines

2. AccessPatterns

3. Nanophotonics

4. Microserver

5. Accelerators

6. NewAlgorithms

7. Real-TimeCommunications

5-year Research Project: 76 IBM PY (32 in NL); 50 ASTRON PY

PISAPlatform-Independent

Software Analysis

workload properties ExaBounds system results

ExtrAX

Modeling – Tool Flow

Goal: Create a holistic design-space exploration tool to overcome fundamental technology limits in data centers, servers and exascalesystems by use of a novel formal method that captures first principles in form of equations compounded with boundary conditions (power, required throughput, I/O, technology parameters, architecture).

P1 – Modeling

SKA algorithms analysis→ compute requirements→ power analysis: power budgets hard to meet → power-efficient chip architectures (SKA signal-processing front-end)

+ ExaBounds (SKA back-end: SDP)

Bottom-line:



10


SRC




Modeling


11 Sep 10 2013 IBM Confidential

Access patterns: Data units assignment example (1000 100GB chunks)

Budget = $23,000Mean Response = 0.27 sec

Budget = $35,000Mean Response = 0.0017 sec

l Red: SSDl Green: HDDl Blue: Tape

P2 – Access Patterns

1. Fully analytical model for multi-tier storage system cost/performance calculation:• Used for APERTIF Long Term Archive • Basis for Regional science datacenters for SKA project.

2. Analytical model for performance analysis of predictive caching:• Used for LOFAR Long Term Archive at this momen

• “Cognitive Storage” project.

Bottom-line:



13


SRC




Modeling


Photonics – Overview

Sky Signal

Antenna LNA

ADCADCADCADC

Transport-links Beamforming & Filtering

BFCorrelator/CSP

Signal processing

few to 10 km

Optical Beamforming

Antenna(omnidirectional)

Analog Fiber Links

Sky Signal

Antenna-Element

LNA

LaserSky Signal

Antenna-Element

LNA

Laser

Photonics Beamforming

fiber cable PD

Amplifier

Sky Signal

Antenna-Element

LNA

Laser

Beamforming = Reducing Data: - Electronic/Digital Beamforming «in» the dish= Reducing # cables risks to interfere with signal reception (RFI)

- Optical Beamforming ... does NOT!!

Beamformer Requirements:Frequency Range: ~3 GHzArray Dimensions: 10 x 11 ElementsElement Spacing: 21 mmArray Size: 22.4 x 22.4 cmBeam-Steering: +/- 30º

PhotonicsBeamformer

15 Currently being measured



16


SRC




Modeling


Microserver - DefinitionµServer:

The integration of an entire server node motherboard*

into a single microchip except DRAM, Nor-boot flash and power conversion logic.

305mm

245mm

139mm x55mm x 7mm

This does NOT imply low performance!

* no graphics

138mm x67mm x 6.9mm

iPhone-6

Ultimate System: 2U rack unit

19” 2U Chassis w/ Combined Cooling & Power128 compute node boards

1536 cores / 3072 Threads6 TB DRAM1.28Tbps Ethernet (@40Gbps)à Datacenter-in-a-box

40% more performance @ 70% of node level energy consumption à 2x more operations per Watt

4.4: Energy-Efficient Microserver Based on a 12-Core 1.8GHz 188K-CoreMark 28nm Bulk CMOS 64b SoCfor Big-Data Applications with 159GB/s/L Memory Bandwidth System Density

2015 IEEE International Solid-State Circuits Conference

Followed through: ILA microservers start-up



19


SRC




Modeling


Image-Domain griddingExplore inherent parallelism in gridding...?

Convolution in Fourier Domain = multiplication in image domain

• ~32 x 32 subgrids

• Local memory• parallelism

subgrid

subgrid

It works !

Status: • On GPU (!) 25x faster then LOFAR (CPU) imager• Imager for LOFAR

Image courtesy of Bas van der Tol



21


SRC




Modeling


22 Sep 10 2013 IBM Confidential

Basic Algorithms:



23


SRC




Modeling


RDMA

ScientificDataProcessing

DataCorrelation

3

21

Efficiency of data transport1. Power consumption of data transfer and processing2. Efficient data transfer to data processing entity3. Intermediate ingress data buffering at proc. Entity4. Use of Flash as ingress data buffer.5. Underlying technologies for Spark.

1. 7 Very active workstreams with focus on SKA• 130+ Scientific (peer reviewed) publications since start, many more accepted & in

preparation,

• DOME impact on SDP – SKA1:• Performance modelling• SDP (and SKA) architecture – re-baselining• Image Domain gridding on accelerators• Microserver as data center in a box• RDMA for energy efficient data transport• Near-memory computing• Fundamental algorithm research• Optical transmission antennae – CSP/station-processing• Balance new vs. existing technologies• Technology vision• Energy Focus

• DOME impact on SKA-2:• ASIC’s, DSP• Nanophotonics & optical beamforming• Algorithms for beamforming and calibration• RDMA• Microservers/microdata centers

8 dome results · dome project: dome research streams… 1. algorithms & machines 2. access...

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