SlideShare a Scribd company logo
15th ANNUAL WORKSHOP 2019
TO HDR AND BEYOND
Ariel Almog, Software Architect
March, 2019
Mellanox Technologies
NETWORK DATA RATE IS EXPANDING
2 OpenFabrics Alliance Workshop 2019
▪ Network data rate is duplicated every 3 years
• SDR – 2.5 Gbps per lane, 2001
• DDR – 5 Gbps per lane, 2005
• QDR – 10 Gbps per lane, 2007
• FDR – 14 Gbps per lane, 2011
• EDR – 25 Gbps per lane, 2014
• HDR – 50 Gbps per lane, 2018
▪ Each new rate exposes new
types of modules
TYPES OF INTERCONNECT
Direct Attach Coax (DAC)
“Transceiver”
1/4/8-chennels Transmit
1/4/8-channels Receiver
Copper Wires.
Directly Attaches one system to another
Key feature = Lowest Cost
Limit = 3m @ 25G rates
Optical Transceiver
Converts electrical signals to optical.
Transmits blinking laser light over optical fiber.
Key feature = long reach.
Limit = Higher cost, higher power
Active Optical Cable
2 Transceivers with optical fiber glued in.
Key feature = Lowest Cost Optical
Limit = 100m
4X/1X FORM FACTORS
▪ Defined by SFF Committee / MSA (Multiple Source Agreement)
▪ QSFP – Quad Small Formfactor Pluggable
• 4 electrical lanes
• QSFP28 : 25G-28G per channel
• QSFP+ : 10G-14G per channel
▪ SFP – Small Formfactor Pluggable
• 1 electrical lane
• SFP28 : 25G per channel
• SFP+ : 10G per channel
FORM FACTORS – WHAT’S NEW
▪ QSFP-DD (QSFP Double Density)
• 8X electrical lanes connector
• Backward compatible to QSFP modules
• Up to 12W, 36 in 1U
▪ OSFP (Octal Small Form Factor Pluggable)
• 8X electrical lanes connector
• Wider than QSFP
• Up to 15W, 36 in 1U
▪ COBO (Consortium for On-Board Optics)
• 8x on board optics
▪ All 3 form factor target to share the same management interface
▪ QSFP-DD showed already POCs of systems, copper
▪ Other
• QSFP / SFP will be used also for 50G/lane (based on QSFP28/SFP28)
• SFP-DD – recently initiated
• uQSFP up to 5W, 4 lanes, 72 in 1U (SFP width)
COPPER CABLES – DAC (DIRECT ATTACH CABLE)
▪ “Simple” copper connection between two ends of the link.
• No active electronics or optics – simplest construction
• Zero power consumption – no active elements
▪ Copper cables properties:
• AWG (American wire gauge)
• 26 AWG
• 28 AWG
• 30 AWG
• Attenuation / loss
• In dB units per frequency
• Cable Length
• For EDR up to 5m (typical 3m)
• For HDR / 200GE up to 3m (2m in IB spec)
▪ Copper cables frequency response limits
• Can support rates below the max rate*
COPPER CABLES – DAC (DIRECT ATTACH CABLE)
▪ Straight Copper configurations:
• QSFP28 <-> QSFP28
• SFP28 <-> SFP28
• QSFP-to-SFP port adapters & cables
▪ Splitter configurations:
• QSFP28 <-> 2 x QSFP28
(half populated)
• QSFP28 <-> 4 x SFP28
▪ Copper cable has an EEPROM
• Identification
• Vendor Name
• Part Number
• Serial Number
• Date of production
• Max supported rate
• Length
• Attenuation
• Near-End / Far-End configuration
Cable’s
EEPROM
WHY IS OPTICAL COMMUNICATION NEEDED
▪ Reach - Typical datacenter layout
• Minimum reach inside the rack (between TOR to HCA) – 3m
• Between racks to ‘Leaf’ switch – up to 30m
• Between Leaf switch to Spine switch – up to 100m
MULTIMODE VS SINGLEMODE
▪ Modal dispersion – each mode propagates in a different speed through the core =>
Pulse spreading.
▪ Chromatic dispersion – light source is never monochromatic. Each color propagates at
a different speed
MULTIMODE VS SINGLEMODE
Parameter Multimode Singlemode
Dispersion Modal + Chromatic Chromatic only
Light coupling Easy Challenging
Fiber cost A bit higher A bit lower
Light source cost Lower Higher
Typical wavelength 850 nm 1310 nm / 1550 nm
Overall transceiver cost Lower Higher
Reach 100s of meters Many KMs
WDM Yes* Yes
KEY PARAMETERS OF OPTICAL TRANSCEIVER
▪ BER – Bit Error Rate
• Bit Error = deciding on ‘0’ when actually ‘1’ was transmitted (or vise versa)
• BER = what is the ratio between bit errors and good bits
• Typical BER requirement is 10-12 (1 error in every 1012 transmitted bits)
• Optical Link budget defines the optical power we have to spare while keeping a minimum BER requirement.
▪ FEC – Forward Error Correction
• Adds extra/redundant information to a transmission so that a receiver can “ recover ” from small errors
• Today, done at the host only, not in the transceiver
• Costs latency (more processing to do on the bit stream, even when there are no error)
ETHERNET PROTOCOLS CONVENTIONS
▪ XXX - MAC speed:
• 10 / 50 / 100 / 200 / 400
▪ M - Media type:
• C - copper, K - backplane, S - MMF optics, L - 10km SMF optics, D - 500m SMF optics, F - 2km SMF
▪ E - Encoding:
• R – 64/66 (and all new protocols), X – 8/10 encoding (1G / legacy 10G “XAUI”)
▪ N – Number of physical (PMA) lanes
• 1 (not written) / 2 / 4 / 8
▪ Examples: 100GBASE-SR4, 400GBASE-DR4, 25GBASE-CR
▪ AUIs:
• chipmodule / chipchip: 25GAUI, 400GAUI-8, CAUI-4
▪ Most protocol names follow the above scheme, however spec wise it’s just a name.
XXX BASE- M E N
ETHERNET PROTOCOLS (BUT THERE ARE MANY MORE…)
Phy (PMD) Description Number of
wavelengths
Number of Fibers /
Copper channels per
RX/TX
Passive
50GBASE-CR Copper up to 3m - 1 pairs
100GBASE-CR2 - 2 pairs
100GBASE-CR4 - 4 pairs
200GBASE-CR4 - 4 pairs
MMF*
50GBASE-SR 50G per λ 1 1
100GBASE-SR2 50G per λ parallel 2 2
200GBASE-SR4 50G per λ parallel 4 4
SMF
500m
100GBASE-DR 100G per λ 1 1
200GBASE-DR4 50G per λ PSM4 4 4
400GBASE-DR4 100G per λ PSM4 4 4
SMF
2km-10km
50GBASE-FR / LR 50G per λ 1 1
200GBASE-FR4 / LR4 50G per λ WDM4 4 1
400GBASE-FR8 / LR8 50G per λ WDM8 8 1
EXPOSING NEW MODULE IN OS
• Linux configuration is done through ethtool
• Ethernet interfaces and partial support in Infiniband
• ethtool -s devname speed N [duplex
half|full] [port tp|aui|bnc|mii]
[autoneg on|off] [advertise N]
• Current appearance shall be changed as It doesn’t scale
• For example, for 200 Gbs (4 * 50) around 20
permutation can be found
• AN and advertised is limited
• Duplex
• --eeprom-dump
• Support for e2prom parsing for new type of msa
• Other OSs (Windows, freebsd)
CONNECTX-5 SOCKET DIRECT - SYSTEM USAGE
▪ 100Gb/s network adapters
• Use two PCIe x8 slots
• Adapter and PCI extender connected by harness
▪ Both CPU’s directly connect to the
network
• Improved performance
• Enables GPU / peer direct on both slots
▪ Each PCIe bus is connected through
different NUMA node
▪ For OS, exposed as 2 or more net_device
each with it’s own associated RDMA
device
▪ Application enjoy direct device to local
NUMA access
▪ Ordering OPN
• MCX556M-ECAT_S25
• MCX556M-ECAT_S35A
• With active auxiliary card
CPU CPU
QPI
CPU CPU
QPI
Network
Applications Applications
Bottleneck
CPU CPU
QPI
CPU CPU
QPI
Network
Applications Applications
QPI QPI
MULTI-PCI SOCKET NIC - TRANSPARENCY TO THE APP
▪ Application use & feel – would like to work with single net I/F
▪ Use Linux bonding with RDMA device bonding
▪ For TCP/IP traffic
• On TX, select slave according to TX queue affinity
• On RX, use accelerated RFS to educate the NIC which slave to use per flow
▪ For RDMA/User mode ETH (Verbs/DPDK) traffic select slave
according to:
• Explicit - Transport object (QP) logical port create affinity attribute
• Or transport object creation thread CPU affinity attribute
• QPn namespace is divided across slaves
• On receive use QPn to slave mapping
• From BTH or from Flow Steering action
▪ Don’t share HW resources (CQ, SRQ) on different CPU
sockets
• each device has it’s own HW resources
eth0
Phys
Port
PCIe
PF0
eth1
Linux Bonding/
Teaming
PCIe
PF1
HW
Bond
RDMA
Device
RDMA
Device
bond0
RDMA
Device
NIC
MULTI-HOST SOCKET DIRECTTM BENCHMARKS
CPU CPU CPU CPUQPI
Network
Applications Applications
Local CPU Test Setup
QPI
CPU CPU CPU CPU
QPI
Network
Applications Applications
Socket Direct Test Setup
QPI
CPU CPU CPU CPUQPI
Network
Applications Applications
Remote CPU Test Setup
QPI
• Reduced Latency
• Reduced CPU Utilization
• Better Throughput
• Increased available QPI bandwidth
Applications Applications
SOCKET DIRECT ADAPTER – AVERAGE LATENCY
Lowerisbetter
SOCKET DIRECT ADAPTER – CPU UTILIZATION
Up to 50% CPU Utilization Improvement
Lowerisbetter
SOCKET DIRECT ADAPTER – NETWORK THROUGHPUT
16% Network Throughout Improvement
Higherisbetter
BENCHMARK SETUP DETAILS
Component Description
Gen3 System Dell PowerEdge R730
CPU Intel(R) Xeon(R) CPU E5-2687W v4 @ 3.00GHz
Number of cores 24
Distribution name Red_Hat_Enterprise_Linux_Server_release_7.3
Driver version MLNX_OFED_LINUX-4.0-0.1.2.0
Firmware 12.18.1000
MTU 1500B
PCIe Gen3
Width x16 / x8
Mellanox adapter ConnectX-4 MCX456A-ECAT / MCX456M-ECAT
15th ANNUAL WORKSHOP 2019
THANK YOU
Ariel Almog, Software Architect
Mellanox Technologies

More Related Content

What's hot

MPLS + BGP Presentation
MPLS + BGP PresentationMPLS + BGP Presentation
MPLS + BGP Presentation
Gino McCarty
 
Dell networking optics and cables connectivity guide
Dell networking optics and cables connectivity guideDell networking optics and cables connectivity guide
Dell networking optics and cables connectivity guide
David Pasek
 
Nokia L3 VPN Configuration Guide
Nokia L3 VPN Configuration GuideNokia L3 VPN Configuration Guide
Nokia L3 VPN Configuration Guide
Abel Saduwa
 
400 Gigabits Ethernet
400 Gigabits Ethernet400 Gigabits Ethernet
400 Gigabits Ethernet
Dhiman Chowdhury
 
How networks are build
How networks are buildHow networks are build
How networks are build
Mike Siowa
 
Fiber Technology Trends for Next Generation Networks
Fiber Technology Trends for Next Generation NetworksFiber Technology Trends for Next Generation Networks
Fiber Technology Trends for Next Generation NetworksCPqD
 
CEI-56G - Testing Considerations
CEI-56G - Testing Considerations CEI-56G - Testing Considerations
CEI-56G - Testing Considerations
Deborah Porchivina
 
Inter-AS MPLS VPN Deployment
Inter-AS MPLS VPN DeploymentInter-AS MPLS VPN Deployment
Inter-AS MPLS VPN Deployment
Bangladesh Network Operators Group
 
Metro High-Speed Product Line Manager
Metro High-Speed Product Line ManagerMetro High-Speed Product Line Manager
Metro High-Speed Product Line Manager
CPqD
 
Next Generation Optical Networking: Software-Defined Optical Networking
Next Generation Optical Networking: Software-Defined Optical NetworkingNext Generation Optical Networking: Software-Defined Optical Networking
Next Generation Optical Networking: Software-Defined Optical Networking
ADVA
 
ENRZ Advanced Modulation for Low Latency Applications
ENRZ Advanced Modulation for Low Latency ApplicationsENRZ Advanced Modulation for Low Latency Applications
ENRZ Advanced Modulation for Low Latency Applications
Deborah Porchivina
 
Mpls
MplsMpls
Routing Protocols and Concepts: Ch9 - EIGRP
Routing Protocols and Concepts: Ch9 - EIGRPRouting Protocols and Concepts: Ch9 - EIGRP
Routing Protocols and Concepts: Ch9 - EIGRP
Abdelkhalik Mosa
 
MPLS L3 VPN Tutorial, by Nurul Islam Roman [APNIC 38]
MPLS L3 VPN Tutorial, by Nurul Islam Roman [APNIC 38]MPLS L3 VPN Tutorial, by Nurul Islam Roman [APNIC 38]
MPLS L3 VPN Tutorial, by Nurul Islam Roman [APNIC 38]
APNIC
 
PLNOG 17 - Marek Janik - Sieć dla IXP
PLNOG 17 - Marek Janik - Sieć dla IXPPLNOG 17 - Marek Janik - Sieć dla IXP
PLNOG 17 - Marek Janik - Sieć dla IXP
PROIDEA
 
Mpls L3_vpn
Mpls L3_vpnMpls L3_vpn
Mpls L3_vpn
Reza Farahani
 
Nokia LTE IP Planning Guide
Nokia LTE IP Planning GuideNokia LTE IP Planning Guide
Nokia LTE IP Planning Guide
Tarun Sharma - CCNA®, ITIL®, ETCP
 
Cisco Live! :: Deploying SIP Trunks with Cisco Unified Border Element (CUBE/v...
Cisco Live! :: Deploying SIP Trunks with Cisco Unified Border Element (CUBE/v...Cisco Live! :: Deploying SIP Trunks with Cisco Unified Border Element (CUBE/v...
Cisco Live! :: Deploying SIP Trunks with Cisco Unified Border Element (CUBE/v...
Bruno Teixeira
 

What's hot (20)

MPLS + BGP Presentation
MPLS + BGP PresentationMPLS + BGP Presentation
MPLS + BGP Presentation
 
Dell networking optics and cables connectivity guide
Dell networking optics and cables connectivity guideDell networking optics and cables connectivity guide
Dell networking optics and cables connectivity guide
 
Nokia L3 VPN Configuration Guide
Nokia L3 VPN Configuration GuideNokia L3 VPN Configuration Guide
Nokia L3 VPN Configuration Guide
 
400 Gigabits Ethernet
400 Gigabits Ethernet400 Gigabits Ethernet
400 Gigabits Ethernet
 
How networks are build
How networks are buildHow networks are build
How networks are build
 
Fiber Technology Trends for Next Generation Networks
Fiber Technology Trends for Next Generation NetworksFiber Technology Trends for Next Generation Networks
Fiber Technology Trends for Next Generation Networks
 
CEI-56G - Testing Considerations
CEI-56G - Testing Considerations CEI-56G - Testing Considerations
CEI-56G - Testing Considerations
 
Inter-AS MPLS VPN Deployment
Inter-AS MPLS VPN DeploymentInter-AS MPLS VPN Deployment
Inter-AS MPLS VPN Deployment
 
Metro High-Speed Product Line Manager
Metro High-Speed Product Line ManagerMetro High-Speed Product Line Manager
Metro High-Speed Product Line Manager
 
Next Generation Optical Networking: Software-Defined Optical Networking
Next Generation Optical Networking: Software-Defined Optical NetworkingNext Generation Optical Networking: Software-Defined Optical Networking
Next Generation Optical Networking: Software-Defined Optical Networking
 
ENRZ Advanced Modulation for Low Latency Applications
ENRZ Advanced Modulation for Low Latency ApplicationsENRZ Advanced Modulation for Low Latency Applications
ENRZ Advanced Modulation for Low Latency Applications
 
Metro Ethernet Concepts
Metro Ethernet ConceptsMetro Ethernet Concepts
Metro Ethernet Concepts
 
Mpls
MplsMpls
Mpls
 
Routing Protocols and Concepts: Ch9 - EIGRP
Routing Protocols and Concepts: Ch9 - EIGRPRouting Protocols and Concepts: Ch9 - EIGRP
Routing Protocols and Concepts: Ch9 - EIGRP
 
MPLS L3 VPN Tutorial, by Nurul Islam Roman [APNIC 38]
MPLS L3 VPN Tutorial, by Nurul Islam Roman [APNIC 38]MPLS L3 VPN Tutorial, by Nurul Islam Roman [APNIC 38]
MPLS L3 VPN Tutorial, by Nurul Islam Roman [APNIC 38]
 
PLNOG 17 - Marek Janik - Sieć dla IXP
PLNOG 17 - Marek Janik - Sieć dla IXPPLNOG 17 - Marek Janik - Sieć dla IXP
PLNOG 17 - Marek Janik - Sieć dla IXP
 
Ieee 802.11.n
Ieee 802.11.nIeee 802.11.n
Ieee 802.11.n
 
Mpls L3_vpn
Mpls L3_vpnMpls L3_vpn
Mpls L3_vpn
 
Nokia LTE IP Planning Guide
Nokia LTE IP Planning GuideNokia LTE IP Planning Guide
Nokia LTE IP Planning Guide
 
Cisco Live! :: Deploying SIP Trunks with Cisco Unified Border Element (CUBE/v...
Cisco Live! :: Deploying SIP Trunks with Cisco Unified Border Element (CUBE/v...Cisco Live! :: Deploying SIP Trunks with Cisco Unified Border Element (CUBE/v...
Cisco Live! :: Deploying SIP Trunks with Cisco Unified Border Element (CUBE/v...
 

Similar to To HDR and Beyond

400G/800G High Speed Networking product guide
400G/800G High Speed Networking product guide400G/800G High Speed Networking product guide
400G/800G High Speed Networking product guide
MITS Component & System Corp.
 
Next-generation-Interconnects-the-Critical-Importance-of-Cables-and-Connectors
Next-generation-Interconnects-the-Critical-Importance-of-Cables-and-ConnectorsNext-generation-Interconnects-the-Critical-Importance-of-Cables-and-Connectors
Next-generation-Interconnects-the-Critical-Importance-of-Cables-and-Connectors
ssuser6d7b1f3
 
20190409 ip showcase-nab19_m3_l-currentstatus-st2110-over-25gbe_v100
20190409 ip showcase-nab19_m3_l-currentstatus-st2110-over-25gbe_v10020190409 ip showcase-nab19_m3_l-currentstatus-st2110-over-25gbe_v100
20190409 ip showcase-nab19_m3_l-currentstatus-st2110-over-25gbe_v100
M3L Inc.
 
PLNOG 13: Alexis Dacquay: Handling high-bandwidth-consumption applications in...
PLNOG 13: Alexis Dacquay: Handling high-bandwidth-consumption applications in...PLNOG 13: Alexis Dacquay: Handling high-bandwidth-consumption applications in...
PLNOG 13: Alexis Dacquay: Handling high-bandwidth-consumption applications in...
PROIDEA
 
Silicon Photonics for Extreme Computing - Challenges and Opportunities
Silicon Photonics for Extreme Computing - Challenges and OpportunitiesSilicon Photonics for Extreme Computing - Challenges and Opportunities
Silicon Photonics for Extreme Computing - Challenges and Opportunities
inside-BigData.com
 
Next Generation Fiber Structured Cabling and Migration to 40/100g
Next Generation Fiber Structured Cabling and Migration to 40/100gNext Generation Fiber Structured Cabling and Migration to 40/100g
Next Generation Fiber Structured Cabling and Migration to 40/100g
Panduit
 
Gigalight Solutions for Data Center and Cloud Computing
Gigalight Solutions for Data Center and Cloud ComputingGigalight Solutions for Data Center and Cloud Computing
Gigalight Solutions for Data Center and Cloud Computing
Gigalight
 
05. DF - Latest Trends in Optical Data Center Interconnects
05. DF - Latest Trends in Optical Data Center Interconnects05. DF - Latest Trends in Optical Data Center Interconnects
05. DF - Latest Trends in Optical Data Center InterconnectsDimitris Filippou
 
Optical networking
Optical networkingOptical networking
Optical networking
Fawzi Mohammed Hassan
 
Mits 5G brief solution 2021
Mits 5G brief solution 2021Mits 5G brief solution 2021
Mits 5G brief solution 2021
MITS Component & System Corp.
 
Sspi day out_2014_advantech-mario_jorge
Sspi day out_2014_advantech-mario_jorgeSspi day out_2014_advantech-mario_jorge
Sspi day out_2014_advantech-mario_jorge
SSPI Brasil
 
Chap.1 ethernet introduction
Chap.1 ethernet introductionChap.1 ethernet introduction
Chap.1 ethernet introduction
東原 李
 
100G QSFP28 Optical Transceiver Data Sheet By JTOPTICS
100G QSFP28 Optical Transceiver Data Sheet By JTOPTICS100G QSFP28 Optical Transceiver Data Sheet By JTOPTICS
100G QSFP28 Optical Transceiver Data Sheet By JTOPTICS
Jayani Technologies Ltd
 
5 g ran_jnn_atal_fdp
5 g ran_jnn_atal_fdp5 g ran_jnn_atal_fdp
5 g ran_jnn_atal_fdp
SureshaVSathegala
 
Vsat day-2008-comtech
Vsat day-2008-comtechVsat day-2008-comtech
Vsat day-2008-comtech
SSPI Brasil
 
LTE-Advanced Physical Layer
LTE-Advanced Physical LayerLTE-Advanced Physical Layer
LTE-Advanced Physical Layer
Praveen Kumar
 
SDM – A New (Subsea) Cable Paradigm
SDM – A New (Subsea) Cable ParadigmSDM – A New (Subsea) Cable Paradigm
SDM – A New (Subsea) Cable Paradigm
MyNOG
 
Zigbee intro v5
Zigbee intro v5Zigbee intro v5
Zigbee intro v5rajrayala
 
Siae Company Overview
Siae Company OverviewSiae Company Overview

Similar to To HDR and Beyond (20)

400G/800G High Speed Networking product guide
400G/800G High Speed Networking product guide400G/800G High Speed Networking product guide
400G/800G High Speed Networking product guide
 
Next-generation-Interconnects-the-Critical-Importance-of-Cables-and-Connectors
Next-generation-Interconnects-the-Critical-Importance-of-Cables-and-ConnectorsNext-generation-Interconnects-the-Critical-Importance-of-Cables-and-Connectors
Next-generation-Interconnects-the-Critical-Importance-of-Cables-and-Connectors
 
20190409 ip showcase-nab19_m3_l-currentstatus-st2110-over-25gbe_v100
20190409 ip showcase-nab19_m3_l-currentstatus-st2110-over-25gbe_v10020190409 ip showcase-nab19_m3_l-currentstatus-st2110-over-25gbe_v100
20190409 ip showcase-nab19_m3_l-currentstatus-st2110-over-25gbe_v100
 
PLNOG 13: Alexis Dacquay: Handling high-bandwidth-consumption applications in...
PLNOG 13: Alexis Dacquay: Handling high-bandwidth-consumption applications in...PLNOG 13: Alexis Dacquay: Handling high-bandwidth-consumption applications in...
PLNOG 13: Alexis Dacquay: Handling high-bandwidth-consumption applications in...
 
Silicon Photonics for Extreme Computing - Challenges and Opportunities
Silicon Photonics for Extreme Computing - Challenges and OpportunitiesSilicon Photonics for Extreme Computing - Challenges and Opportunities
Silicon Photonics for Extreme Computing - Challenges and Opportunities
 
Next Generation Fiber Structured Cabling and Migration to 40/100g
Next Generation Fiber Structured Cabling and Migration to 40/100gNext Generation Fiber Structured Cabling and Migration to 40/100g
Next Generation Fiber Structured Cabling and Migration to 40/100g
 
Gigalight Solutions for Data Center and Cloud Computing
Gigalight Solutions for Data Center and Cloud ComputingGigalight Solutions for Data Center and Cloud Computing
Gigalight Solutions for Data Center and Cloud Computing
 
05. DF - Latest Trends in Optical Data Center Interconnects
05. DF - Latest Trends in Optical Data Center Interconnects05. DF - Latest Trends in Optical Data Center Interconnects
05. DF - Latest Trends in Optical Data Center Interconnects
 
Optical networking
Optical networkingOptical networking
Optical networking
 
Mits 5G brief solution 2021
Mits 5G brief solution 2021Mits 5G brief solution 2021
Mits 5G brief solution 2021
 
Sspi day out_2014_advantech-mario_jorge
Sspi day out_2014_advantech-mario_jorgeSspi day out_2014_advantech-mario_jorge
Sspi day out_2014_advantech-mario_jorge
 
Chap.1 ethernet introduction
Chap.1 ethernet introductionChap.1 ethernet introduction
Chap.1 ethernet introduction
 
100G QSFP28 Optical Transceiver Data Sheet By JTOPTICS
100G QSFP28 Optical Transceiver Data Sheet By JTOPTICS100G QSFP28 Optical Transceiver Data Sheet By JTOPTICS
100G QSFP28 Optical Transceiver Data Sheet By JTOPTICS
 
5 g ran_jnn_atal_fdp
5 g ran_jnn_atal_fdp5 g ran_jnn_atal_fdp
5 g ran_jnn_atal_fdp
 
Vsat day-2008-comtech
Vsat day-2008-comtechVsat day-2008-comtech
Vsat day-2008-comtech
 
LTE-Advanced Physical Layer
LTE-Advanced Physical LayerLTE-Advanced Physical Layer
LTE-Advanced Physical Layer
 
Ultra_Wide_Band_ppt
Ultra_Wide_Band_pptUltra_Wide_Band_ppt
Ultra_Wide_Band_ppt
 
SDM – A New (Subsea) Cable Paradigm
SDM – A New (Subsea) Cable ParadigmSDM – A New (Subsea) Cable Paradigm
SDM – A New (Subsea) Cable Paradigm
 
Zigbee intro v5
Zigbee intro v5Zigbee intro v5
Zigbee intro v5
 
Siae Company Overview
Siae Company OverviewSiae Company Overview
Siae Company Overview
 

More from inside-BigData.com

Major Market Shifts in IT
Major Market Shifts in ITMajor Market Shifts in IT
Major Market Shifts in IT
inside-BigData.com
 
Preparing to program Aurora at Exascale - Early experiences and future direct...
Preparing to program Aurora at Exascale - Early experiences and future direct...Preparing to program Aurora at Exascale - Early experiences and future direct...
Preparing to program Aurora at Exascale - Early experiences and future direct...
inside-BigData.com
 
Transforming Private 5G Networks
Transforming Private 5G NetworksTransforming Private 5G Networks
Transforming Private 5G Networks
inside-BigData.com
 
The Incorporation of Machine Learning into Scientific Simulations at Lawrence...
The Incorporation of Machine Learning into Scientific Simulations at Lawrence...The Incorporation of Machine Learning into Scientific Simulations at Lawrence...
The Incorporation of Machine Learning into Scientific Simulations at Lawrence...
inside-BigData.com
 
How to Achieve High-Performance, Scalable and Distributed DNN Training on Mod...
How to Achieve High-Performance, Scalable and Distributed DNN Training on Mod...How to Achieve High-Performance, Scalable and Distributed DNN Training on Mod...
How to Achieve High-Performance, Scalable and Distributed DNN Training on Mod...
inside-BigData.com
 
Evolving Cyberinfrastructure, Democratizing Data, and Scaling AI to Catalyze ...
Evolving Cyberinfrastructure, Democratizing Data, and Scaling AI to Catalyze ...Evolving Cyberinfrastructure, Democratizing Data, and Scaling AI to Catalyze ...
Evolving Cyberinfrastructure, Democratizing Data, and Scaling AI to Catalyze ...
inside-BigData.com
 
HPC Impact: EDA Telemetry Neural Networks
HPC Impact: EDA Telemetry Neural NetworksHPC Impact: EDA Telemetry Neural Networks
HPC Impact: EDA Telemetry Neural Networks
inside-BigData.com
 
Biohybrid Robotic Jellyfish for Future Applications in Ocean Monitoring
Biohybrid Robotic Jellyfish for Future Applications in Ocean MonitoringBiohybrid Robotic Jellyfish for Future Applications in Ocean Monitoring
Biohybrid Robotic Jellyfish for Future Applications in Ocean Monitoring
inside-BigData.com
 
Machine Learning for Weather Forecasts
Machine Learning for Weather ForecastsMachine Learning for Weather Forecasts
Machine Learning for Weather Forecasts
inside-BigData.com
 
HPC AI Advisory Council Update
HPC AI Advisory Council UpdateHPC AI Advisory Council Update
HPC AI Advisory Council Update
inside-BigData.com
 
Fugaku Supercomputer joins fight against COVID-19
Fugaku Supercomputer joins fight against COVID-19Fugaku Supercomputer joins fight against COVID-19
Fugaku Supercomputer joins fight against COVID-19
inside-BigData.com
 
Energy Efficient Computing using Dynamic Tuning
Energy Efficient Computing using Dynamic TuningEnergy Efficient Computing using Dynamic Tuning
Energy Efficient Computing using Dynamic Tuning
inside-BigData.com
 
HPC at Scale Enabled by DDN A3i and NVIDIA SuperPOD
HPC at Scale Enabled by DDN A3i and NVIDIA SuperPODHPC at Scale Enabled by DDN A3i and NVIDIA SuperPOD
HPC at Scale Enabled by DDN A3i and NVIDIA SuperPOD
inside-BigData.com
 
State of ARM-based HPC
State of ARM-based HPCState of ARM-based HPC
State of ARM-based HPC
inside-BigData.com
 
Versal Premium ACAP for Network and Cloud Acceleration
Versal Premium ACAP for Network and Cloud AccelerationVersal Premium ACAP for Network and Cloud Acceleration
Versal Premium ACAP for Network and Cloud Acceleration
inside-BigData.com
 
Zettar: Moving Massive Amounts of Data across Any Distance Efficiently
Zettar: Moving Massive Amounts of Data across Any Distance EfficientlyZettar: Moving Massive Amounts of Data across Any Distance Efficiently
Zettar: Moving Massive Amounts of Data across Any Distance Efficiently
inside-BigData.com
 
Scaling TCO in a Post Moore's Era
Scaling TCO in a Post Moore's EraScaling TCO in a Post Moore's Era
Scaling TCO in a Post Moore's Era
inside-BigData.com
 
CUDA-Python and RAPIDS for blazing fast scientific computing
CUDA-Python and RAPIDS for blazing fast scientific computingCUDA-Python and RAPIDS for blazing fast scientific computing
CUDA-Python and RAPIDS for blazing fast scientific computing
inside-BigData.com
 
Introducing HPC with a Raspberry Pi Cluster
Introducing HPC with a Raspberry Pi ClusterIntroducing HPC with a Raspberry Pi Cluster
Introducing HPC with a Raspberry Pi Cluster
inside-BigData.com
 
Overview of HPC Interconnects
Overview of HPC InterconnectsOverview of HPC Interconnects
Overview of HPC Interconnects
inside-BigData.com
 

More from inside-BigData.com (20)

Major Market Shifts in IT
Major Market Shifts in ITMajor Market Shifts in IT
Major Market Shifts in IT
 
Preparing to program Aurora at Exascale - Early experiences and future direct...
Preparing to program Aurora at Exascale - Early experiences and future direct...Preparing to program Aurora at Exascale - Early experiences and future direct...
Preparing to program Aurora at Exascale - Early experiences and future direct...
 
Transforming Private 5G Networks
Transforming Private 5G NetworksTransforming Private 5G Networks
Transforming Private 5G Networks
 
The Incorporation of Machine Learning into Scientific Simulations at Lawrence...
The Incorporation of Machine Learning into Scientific Simulations at Lawrence...The Incorporation of Machine Learning into Scientific Simulations at Lawrence...
The Incorporation of Machine Learning into Scientific Simulations at Lawrence...
 
How to Achieve High-Performance, Scalable and Distributed DNN Training on Mod...
How to Achieve High-Performance, Scalable and Distributed DNN Training on Mod...How to Achieve High-Performance, Scalable and Distributed DNN Training on Mod...
How to Achieve High-Performance, Scalable and Distributed DNN Training on Mod...
 
Evolving Cyberinfrastructure, Democratizing Data, and Scaling AI to Catalyze ...
Evolving Cyberinfrastructure, Democratizing Data, and Scaling AI to Catalyze ...Evolving Cyberinfrastructure, Democratizing Data, and Scaling AI to Catalyze ...
Evolving Cyberinfrastructure, Democratizing Data, and Scaling AI to Catalyze ...
 
HPC Impact: EDA Telemetry Neural Networks
HPC Impact: EDA Telemetry Neural NetworksHPC Impact: EDA Telemetry Neural Networks
HPC Impact: EDA Telemetry Neural Networks
 
Biohybrid Robotic Jellyfish for Future Applications in Ocean Monitoring
Biohybrid Robotic Jellyfish for Future Applications in Ocean MonitoringBiohybrid Robotic Jellyfish for Future Applications in Ocean Monitoring
Biohybrid Robotic Jellyfish for Future Applications in Ocean Monitoring
 
Machine Learning for Weather Forecasts
Machine Learning for Weather ForecastsMachine Learning for Weather Forecasts
Machine Learning for Weather Forecasts
 
HPC AI Advisory Council Update
HPC AI Advisory Council UpdateHPC AI Advisory Council Update
HPC AI Advisory Council Update
 
Fugaku Supercomputer joins fight against COVID-19
Fugaku Supercomputer joins fight against COVID-19Fugaku Supercomputer joins fight against COVID-19
Fugaku Supercomputer joins fight against COVID-19
 
Energy Efficient Computing using Dynamic Tuning
Energy Efficient Computing using Dynamic TuningEnergy Efficient Computing using Dynamic Tuning
Energy Efficient Computing using Dynamic Tuning
 
HPC at Scale Enabled by DDN A3i and NVIDIA SuperPOD
HPC at Scale Enabled by DDN A3i and NVIDIA SuperPODHPC at Scale Enabled by DDN A3i and NVIDIA SuperPOD
HPC at Scale Enabled by DDN A3i and NVIDIA SuperPOD
 
State of ARM-based HPC
State of ARM-based HPCState of ARM-based HPC
State of ARM-based HPC
 
Versal Premium ACAP for Network and Cloud Acceleration
Versal Premium ACAP for Network and Cloud AccelerationVersal Premium ACAP for Network and Cloud Acceleration
Versal Premium ACAP for Network and Cloud Acceleration
 
Zettar: Moving Massive Amounts of Data across Any Distance Efficiently
Zettar: Moving Massive Amounts of Data across Any Distance EfficientlyZettar: Moving Massive Amounts of Data across Any Distance Efficiently
Zettar: Moving Massive Amounts of Data across Any Distance Efficiently
 
Scaling TCO in a Post Moore's Era
Scaling TCO in a Post Moore's EraScaling TCO in a Post Moore's Era
Scaling TCO in a Post Moore's Era
 
CUDA-Python and RAPIDS for blazing fast scientific computing
CUDA-Python and RAPIDS for blazing fast scientific computingCUDA-Python and RAPIDS for blazing fast scientific computing
CUDA-Python and RAPIDS for blazing fast scientific computing
 
Introducing HPC with a Raspberry Pi Cluster
Introducing HPC with a Raspberry Pi ClusterIntroducing HPC with a Raspberry Pi Cluster
Introducing HPC with a Raspberry Pi Cluster
 
Overview of HPC Interconnects
Overview of HPC InterconnectsOverview of HPC Interconnects
Overview of HPC Interconnects
 

Recently uploaded

Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...
Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...
Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...
Thierry Lestable
 
Unsubscribed: Combat Subscription Fatigue With a Membership Mentality by Head...
Unsubscribed: Combat Subscription Fatigue With a Membership Mentality by Head...Unsubscribed: Combat Subscription Fatigue With a Membership Mentality by Head...
Unsubscribed: Combat Subscription Fatigue With a Membership Mentality by Head...
Product School
 
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...
James Anderson
 
FIDO Alliance Osaka Seminar: FIDO Security Aspects.pdf
FIDO Alliance Osaka Seminar: FIDO Security Aspects.pdfFIDO Alliance Osaka Seminar: FIDO Security Aspects.pdf
FIDO Alliance Osaka Seminar: FIDO Security Aspects.pdf
FIDO Alliance
 
UiPath Test Automation using UiPath Test Suite series, part 3
UiPath Test Automation using UiPath Test Suite series, part 3UiPath Test Automation using UiPath Test Suite series, part 3
UiPath Test Automation using UiPath Test Suite series, part 3
DianaGray10
 
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
DanBrown980551
 
DevOps and Testing slides at DASA Connect
DevOps and Testing slides at DASA ConnectDevOps and Testing slides at DASA Connect
DevOps and Testing slides at DASA Connect
Kari Kakkonen
 
JMeter webinar - integration with InfluxDB and Grafana
JMeter webinar - integration with InfluxDB and GrafanaJMeter webinar - integration with InfluxDB and Grafana
JMeter webinar - integration with InfluxDB and Grafana
RTTS
 
Epistemic Interaction - tuning interfaces to provide information for AI support
Epistemic Interaction - tuning interfaces to provide information for AI supportEpistemic Interaction - tuning interfaces to provide information for AI support
Epistemic Interaction - tuning interfaces to provide information for AI support
Alan Dix
 
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered Quality
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualitySoftware Delivery At the Speed of AI: Inflectra Invests In AI-Powered Quality
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered Quality
Inflectra
 
Mission to Decommission: Importance of Decommissioning Products to Increase E...
Mission to Decommission: Importance of Decommissioning Products to Increase E...Mission to Decommission: Importance of Decommissioning Products to Increase E...
Mission to Decommission: Importance of Decommissioning Products to Increase E...
Product School
 
Connector Corner: Automate dynamic content and events by pushing a button
Connector Corner: Automate dynamic content and events by pushing a buttonConnector Corner: Automate dynamic content and events by pushing a button
Connector Corner: Automate dynamic content and events by pushing a button
DianaGray10
 
Neuro-symbolic is not enough, we need neuro-*semantic*
Neuro-symbolic is not enough, we need neuro-*semantic*Neuro-symbolic is not enough, we need neuro-*semantic*
Neuro-symbolic is not enough, we need neuro-*semantic*
Frank van Harmelen
 
Assuring Contact Center Experiences for Your Customers With ThousandEyes
Assuring Contact Center Experiences for Your Customers With ThousandEyesAssuring Contact Center Experiences for Your Customers With ThousandEyes
Assuring Contact Center Experiences for Your Customers With ThousandEyes
ThousandEyes
 
Transcript: Selling digital books in 2024: Insights from industry leaders - T...
Transcript: Selling digital books in 2024: Insights from industry leaders - T...Transcript: Selling digital books in 2024: Insights from industry leaders - T...
Transcript: Selling digital books in 2024: Insights from industry leaders - T...
BookNet Canada
 
De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...
De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...
De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...
Product School
 
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Albert Hoitingh
 
Securing your Kubernetes cluster_ a step-by-step guide to success !
Securing your Kubernetes cluster_ a step-by-step guide to success !Securing your Kubernetes cluster_ a step-by-step guide to success !
Securing your Kubernetes cluster_ a step-by-step guide to success !
KatiaHIMEUR1
 
From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...
From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...
From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...
Product School
 
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...
UiPathCommunity
 

Recently uploaded (20)

Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...
Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...
Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...
 
Unsubscribed: Combat Subscription Fatigue With a Membership Mentality by Head...
Unsubscribed: Combat Subscription Fatigue With a Membership Mentality by Head...Unsubscribed: Combat Subscription Fatigue With a Membership Mentality by Head...
Unsubscribed: Combat Subscription Fatigue With a Membership Mentality by Head...
 
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...
 
FIDO Alliance Osaka Seminar: FIDO Security Aspects.pdf
FIDO Alliance Osaka Seminar: FIDO Security Aspects.pdfFIDO Alliance Osaka Seminar: FIDO Security Aspects.pdf
FIDO Alliance Osaka Seminar: FIDO Security Aspects.pdf
 
UiPath Test Automation using UiPath Test Suite series, part 3
UiPath Test Automation using UiPath Test Suite series, part 3UiPath Test Automation using UiPath Test Suite series, part 3
UiPath Test Automation using UiPath Test Suite series, part 3
 
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
 
DevOps and Testing slides at DASA Connect
DevOps and Testing slides at DASA ConnectDevOps and Testing slides at DASA Connect
DevOps and Testing slides at DASA Connect
 
JMeter webinar - integration with InfluxDB and Grafana
JMeter webinar - integration with InfluxDB and GrafanaJMeter webinar - integration with InfluxDB and Grafana
JMeter webinar - integration with InfluxDB and Grafana
 
Epistemic Interaction - tuning interfaces to provide information for AI support
Epistemic Interaction - tuning interfaces to provide information for AI supportEpistemic Interaction - tuning interfaces to provide information for AI support
Epistemic Interaction - tuning interfaces to provide information for AI support
 
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered Quality
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualitySoftware Delivery At the Speed of AI: Inflectra Invests In AI-Powered Quality
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered Quality
 
Mission to Decommission: Importance of Decommissioning Products to Increase E...
Mission to Decommission: Importance of Decommissioning Products to Increase E...Mission to Decommission: Importance of Decommissioning Products to Increase E...
Mission to Decommission: Importance of Decommissioning Products to Increase E...
 
Connector Corner: Automate dynamic content and events by pushing a button
Connector Corner: Automate dynamic content and events by pushing a buttonConnector Corner: Automate dynamic content and events by pushing a button
Connector Corner: Automate dynamic content and events by pushing a button
 
Neuro-symbolic is not enough, we need neuro-*semantic*
Neuro-symbolic is not enough, we need neuro-*semantic*Neuro-symbolic is not enough, we need neuro-*semantic*
Neuro-symbolic is not enough, we need neuro-*semantic*
 
Assuring Contact Center Experiences for Your Customers With ThousandEyes
Assuring Contact Center Experiences for Your Customers With ThousandEyesAssuring Contact Center Experiences for Your Customers With ThousandEyes
Assuring Contact Center Experiences for Your Customers With ThousandEyes
 
Transcript: Selling digital books in 2024: Insights from industry leaders - T...
Transcript: Selling digital books in 2024: Insights from industry leaders - T...Transcript: Selling digital books in 2024: Insights from industry leaders - T...
Transcript: Selling digital books in 2024: Insights from industry leaders - T...
 
De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...
De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...
De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...
 
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
 
Securing your Kubernetes cluster_ a step-by-step guide to success !
Securing your Kubernetes cluster_ a step-by-step guide to success !Securing your Kubernetes cluster_ a step-by-step guide to success !
Securing your Kubernetes cluster_ a step-by-step guide to success !
 
From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...
From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...
From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...
 
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...
 

To HDR and Beyond

  • 1. 15th ANNUAL WORKSHOP 2019 TO HDR AND BEYOND Ariel Almog, Software Architect March, 2019 Mellanox Technologies
  • 2. NETWORK DATA RATE IS EXPANDING 2 OpenFabrics Alliance Workshop 2019 ▪ Network data rate is duplicated every 3 years • SDR – 2.5 Gbps per lane, 2001 • DDR – 5 Gbps per lane, 2005 • QDR – 10 Gbps per lane, 2007 • FDR – 14 Gbps per lane, 2011 • EDR – 25 Gbps per lane, 2014 • HDR – 50 Gbps per lane, 2018 ▪ Each new rate exposes new types of modules
  • 3. TYPES OF INTERCONNECT Direct Attach Coax (DAC) “Transceiver” 1/4/8-chennels Transmit 1/4/8-channels Receiver Copper Wires. Directly Attaches one system to another Key feature = Lowest Cost Limit = 3m @ 25G rates Optical Transceiver Converts electrical signals to optical. Transmits blinking laser light over optical fiber. Key feature = long reach. Limit = Higher cost, higher power Active Optical Cable 2 Transceivers with optical fiber glued in. Key feature = Lowest Cost Optical Limit = 100m
  • 4. 4X/1X FORM FACTORS ▪ Defined by SFF Committee / MSA (Multiple Source Agreement) ▪ QSFP – Quad Small Formfactor Pluggable • 4 electrical lanes • QSFP28 : 25G-28G per channel • QSFP+ : 10G-14G per channel ▪ SFP – Small Formfactor Pluggable • 1 electrical lane • SFP28 : 25G per channel • SFP+ : 10G per channel
  • 5. FORM FACTORS – WHAT’S NEW ▪ QSFP-DD (QSFP Double Density) • 8X electrical lanes connector • Backward compatible to QSFP modules • Up to 12W, 36 in 1U ▪ OSFP (Octal Small Form Factor Pluggable) • 8X electrical lanes connector • Wider than QSFP • Up to 15W, 36 in 1U ▪ COBO (Consortium for On-Board Optics) • 8x on board optics ▪ All 3 form factor target to share the same management interface ▪ QSFP-DD showed already POCs of systems, copper ▪ Other • QSFP / SFP will be used also for 50G/lane (based on QSFP28/SFP28) • SFP-DD – recently initiated • uQSFP up to 5W, 4 lanes, 72 in 1U (SFP width)
  • 6. COPPER CABLES – DAC (DIRECT ATTACH CABLE) ▪ “Simple” copper connection between two ends of the link. • No active electronics or optics – simplest construction • Zero power consumption – no active elements ▪ Copper cables properties: • AWG (American wire gauge) • 26 AWG • 28 AWG • 30 AWG • Attenuation / loss • In dB units per frequency • Cable Length • For EDR up to 5m (typical 3m) • For HDR / 200GE up to 3m (2m in IB spec) ▪ Copper cables frequency response limits • Can support rates below the max rate*
  • 7. COPPER CABLES – DAC (DIRECT ATTACH CABLE) ▪ Straight Copper configurations: • QSFP28 <-> QSFP28 • SFP28 <-> SFP28 • QSFP-to-SFP port adapters & cables ▪ Splitter configurations: • QSFP28 <-> 2 x QSFP28 (half populated) • QSFP28 <-> 4 x SFP28 ▪ Copper cable has an EEPROM • Identification • Vendor Name • Part Number • Serial Number • Date of production • Max supported rate • Length • Attenuation • Near-End / Far-End configuration Cable’s EEPROM
  • 8. WHY IS OPTICAL COMMUNICATION NEEDED ▪ Reach - Typical datacenter layout • Minimum reach inside the rack (between TOR to HCA) – 3m • Between racks to ‘Leaf’ switch – up to 30m • Between Leaf switch to Spine switch – up to 100m
  • 9. MULTIMODE VS SINGLEMODE ▪ Modal dispersion – each mode propagates in a different speed through the core => Pulse spreading. ▪ Chromatic dispersion – light source is never monochromatic. Each color propagates at a different speed
  • 10. MULTIMODE VS SINGLEMODE Parameter Multimode Singlemode Dispersion Modal + Chromatic Chromatic only Light coupling Easy Challenging Fiber cost A bit higher A bit lower Light source cost Lower Higher Typical wavelength 850 nm 1310 nm / 1550 nm Overall transceiver cost Lower Higher Reach 100s of meters Many KMs WDM Yes* Yes
  • 11. KEY PARAMETERS OF OPTICAL TRANSCEIVER ▪ BER – Bit Error Rate • Bit Error = deciding on ‘0’ when actually ‘1’ was transmitted (or vise versa) • BER = what is the ratio between bit errors and good bits • Typical BER requirement is 10-12 (1 error in every 1012 transmitted bits) • Optical Link budget defines the optical power we have to spare while keeping a minimum BER requirement. ▪ FEC – Forward Error Correction • Adds extra/redundant information to a transmission so that a receiver can “ recover ” from small errors • Today, done at the host only, not in the transceiver • Costs latency (more processing to do on the bit stream, even when there are no error)
  • 12. ETHERNET PROTOCOLS CONVENTIONS ▪ XXX - MAC speed: • 10 / 50 / 100 / 200 / 400 ▪ M - Media type: • C - copper, K - backplane, S - MMF optics, L - 10km SMF optics, D - 500m SMF optics, F - 2km SMF ▪ E - Encoding: • R – 64/66 (and all new protocols), X – 8/10 encoding (1G / legacy 10G “XAUI”) ▪ N – Number of physical (PMA) lanes • 1 (not written) / 2 / 4 / 8 ▪ Examples: 100GBASE-SR4, 400GBASE-DR4, 25GBASE-CR ▪ AUIs: • chipmodule / chipchip: 25GAUI, 400GAUI-8, CAUI-4 ▪ Most protocol names follow the above scheme, however spec wise it’s just a name. XXX BASE- M E N
  • 13. ETHERNET PROTOCOLS (BUT THERE ARE MANY MORE…) Phy (PMD) Description Number of wavelengths Number of Fibers / Copper channels per RX/TX Passive 50GBASE-CR Copper up to 3m - 1 pairs 100GBASE-CR2 - 2 pairs 100GBASE-CR4 - 4 pairs 200GBASE-CR4 - 4 pairs MMF* 50GBASE-SR 50G per λ 1 1 100GBASE-SR2 50G per λ parallel 2 2 200GBASE-SR4 50G per λ parallel 4 4 SMF 500m 100GBASE-DR 100G per λ 1 1 200GBASE-DR4 50G per λ PSM4 4 4 400GBASE-DR4 100G per λ PSM4 4 4 SMF 2km-10km 50GBASE-FR / LR 50G per λ 1 1 200GBASE-FR4 / LR4 50G per λ WDM4 4 1 400GBASE-FR8 / LR8 50G per λ WDM8 8 1
  • 14. EXPOSING NEW MODULE IN OS • Linux configuration is done through ethtool • Ethernet interfaces and partial support in Infiniband • ethtool -s devname speed N [duplex half|full] [port tp|aui|bnc|mii] [autoneg on|off] [advertise N] • Current appearance shall be changed as It doesn’t scale • For example, for 200 Gbs (4 * 50) around 20 permutation can be found • AN and advertised is limited • Duplex • --eeprom-dump • Support for e2prom parsing for new type of msa • Other OSs (Windows, freebsd)
  • 15. CONNECTX-5 SOCKET DIRECT - SYSTEM USAGE ▪ 100Gb/s network adapters • Use two PCIe x8 slots • Adapter and PCI extender connected by harness ▪ Both CPU’s directly connect to the network • Improved performance • Enables GPU / peer direct on both slots ▪ Each PCIe bus is connected through different NUMA node ▪ For OS, exposed as 2 or more net_device each with it’s own associated RDMA device ▪ Application enjoy direct device to local NUMA access ▪ Ordering OPN • MCX556M-ECAT_S25 • MCX556M-ECAT_S35A • With active auxiliary card CPU CPU QPI CPU CPU QPI Network Applications Applications Bottleneck CPU CPU QPI CPU CPU QPI Network Applications Applications QPI QPI
  • 16. MULTI-PCI SOCKET NIC - TRANSPARENCY TO THE APP ▪ Application use & feel – would like to work with single net I/F ▪ Use Linux bonding with RDMA device bonding ▪ For TCP/IP traffic • On TX, select slave according to TX queue affinity • On RX, use accelerated RFS to educate the NIC which slave to use per flow ▪ For RDMA/User mode ETH (Verbs/DPDK) traffic select slave according to: • Explicit - Transport object (QP) logical port create affinity attribute • Or transport object creation thread CPU affinity attribute • QPn namespace is divided across slaves • On receive use QPn to slave mapping • From BTH or from Flow Steering action ▪ Don’t share HW resources (CQ, SRQ) on different CPU sockets • each device has it’s own HW resources eth0 Phys Port PCIe PF0 eth1 Linux Bonding/ Teaming PCIe PF1 HW Bond RDMA Device RDMA Device bond0 RDMA Device NIC
  • 17. MULTI-HOST SOCKET DIRECTTM BENCHMARKS CPU CPU CPU CPUQPI Network Applications Applications Local CPU Test Setup QPI CPU CPU CPU CPU QPI Network Applications Applications Socket Direct Test Setup QPI CPU CPU CPU CPUQPI Network Applications Applications Remote CPU Test Setup QPI • Reduced Latency • Reduced CPU Utilization • Better Throughput • Increased available QPI bandwidth Applications Applications
  • 18. SOCKET DIRECT ADAPTER – AVERAGE LATENCY Lowerisbetter
  • 19. SOCKET DIRECT ADAPTER – CPU UTILIZATION Up to 50% CPU Utilization Improvement Lowerisbetter
  • 20. SOCKET DIRECT ADAPTER – NETWORK THROUGHPUT 16% Network Throughout Improvement Higherisbetter
  • 21. BENCHMARK SETUP DETAILS Component Description Gen3 System Dell PowerEdge R730 CPU Intel(R) Xeon(R) CPU E5-2687W v4 @ 3.00GHz Number of cores 24 Distribution name Red_Hat_Enterprise_Linux_Server_release_7.3 Driver version MLNX_OFED_LINUX-4.0-0.1.2.0 Firmware 12.18.1000 MTU 1500B PCIe Gen3 Width x16 / x8 Mellanox adapter ConnectX-4 MCX456A-ECAT / MCX456M-ECAT
  • 22. 15th ANNUAL WORKSHOP 2019 THANK YOU Ariel Almog, Software Architect Mellanox Technologies