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Introduction to Parallel Computing (CMSC498X / CMSC818X) Lecture 20: Networks and Communication Abhinav Bhatele, Department of Computer Science Announcements Assignment 3 posted online Only for 818X students Due on November 23


  1. Introduction to Parallel Computing (CMSC498X / CMSC818X) Lecture 20: Networks and Communication Abhinav Bhatele, Department of Computer Science

  2. Announcements • Assignment 3 posted online • Only for 818X students • Due on November 23 • Quiz 2: November 12 Abhinav Bhatele (CMSC498X/CMSC818X) LIVE RECORDING 2

  3. High-speed interconnection networks • Typically supercomputers and HPC clusters are connected by low latency and high bandwidth networks • The connections between nodes form different topologies • Popular topologies: • Fat-tree: Charles Leiserson in 1985 • Mesh and torus networks • Dragonfly networks Abhinav Bhatele (CMSC498X/CMSC818X) LIVE RECORDING 3

  4. Network components • Network interface controller or card • Router or switch • Network cables: copper or optical Abhinav Bhatele (CMSC498X/CMSC818X) LIVE RECORDING 4

  5. N-dimensional mesh / torus networks • Each switch as a small number of nodes connected to it (typically 1) • Each switch has direct links to 2n switches where n is the number of dimensions • Torus = wraparound links • Examples: IBM Blue Gene, Cray X* machines Abhinav Bhatele (CMSC498X/CMSC818X) LIVE RECORDING 5

  6. Fat-tree network • Router radix = k, Number of nodes on each router = k/2 • A pod is a group of k/2 switches, Max. number of pods = k Abhinav Bhatele (CMSC498X/CMSC818X) LIVE RECORDING 6

  7. Fat-tree network • Router radix = k, Number of nodes on each router = k/2 • A pod is a group of k/2 switches, Max. number of pods = k Compute Nodes Abhinav Bhatele (CMSC498X/CMSC818X) LIVE RECORDING 6

  8. Fat-tree network • Router radix = k, Number of nodes on each router = k/2 • A pod is a group of k/2 switches, Max. number of pods = k Compute Nodes Abhinav Bhatele (CMSC498X/CMSC818X) LIVE RECORDING 6

  9. Fat-tree network • Router radix = k, Number of nodes on each router = k/2 • A pod is a group of k/2 switches, Max. number of pods = k Compute Nodes Abhinav Bhatele (CMSC498X/CMSC818X) LIVE RECORDING 6

  10. Fat-tree network • Router radix = k, Number of nodes on each router = k/2 • A pod is a group of k/2 switches, Max. number of pods = k Level 1 Compute Nodes Abhinav Bhatele (CMSC498X/CMSC818X) LIVE RECORDING 6

  11. Fat-tree network • Router radix = k, Number of nodes on each router = k/2 • A pod is a group of k/2 switches, Max. number of pods = k Level 2 Level 1 Compute Nodes Abhinav Bhatele (CMSC498X/CMSC818X) LIVE RECORDING 6

  12. Fat-tree network • Router radix = k, Number of nodes on each router = k/2 • A pod is a group of k/2 switches, Max. number of pods = k Level 2 Level 1 Compute Nodes Abhinav Bhatele (CMSC498X/CMSC818X) LIVE RECORDING 6

  13. Fat-tree network • Router radix = k, Number of nodes on each router = k/2 • A pod is a group of k/2 switches, Max. number of pods = k Level 2 Level 1 Compute Nodes Abhinav Bhatele (CMSC498X/CMSC818X) LIVE RECORDING 6

  14. Fat-tree network • Router radix = k, Number of nodes on each router = k/2 • A pod is a group of k/2 switches, Max. number of pods = k Level 3 Level 2 Level 1 Compute Nodes Abhinav Bhatele (CMSC498X/CMSC818X) LIVE RECORDING 6

  15. Dragonfly network • Two-level hierarchical network using high-radix routers • Low network diameter � � � �� � LL �� � �� � � � � � � � �� � �� � �� � � �� � �� � � � �� � �� � �� � �� � LR �� � �� � �� � �� � �� � �� � �� � �� � �� � �� �� �� � �� � �� �� D �� �� �� �� �� �� �� � �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� � �� �� �� �� � �� �� �� �� � � �� �� �� �� �� � �� �� �� � �� � � � � �� � �� � �� � �� � �� � �� � �� � �� � �� � �� � �� � �� �� �� � �� � �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� � �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� � � � �� � �� � �� � � � � �� � �� � �� � �� � �� �� �� � �� � �� � �� � �� � �� � �� �� �� �� �� � �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� � � � �� �� �� �� �� � �� �� �� �� �� �� � �� � �� � � � �� � �� � �� � �� � �� � �� � �� � �� � �� � �� � �� �� �� � One supernode in the PERCS topology �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� Abhinav Bhatele (CMSC498X/CMSC818X) LIVE RECORDING 7

  16. Life-cycle of a message Source Source Source Source Source Message origin points : destination, frequency, size, etc. determined by application 1 micro sec - 10s of sec Abhinav Bhatele (CMSC498X/CMSC818X) LIVE RECORDING 8

  17. Life-cycle of a message Source Packetization and injection : delay:100s of ns Source NIC Source Source Source Message origin points : destination, frequency, size, etc. determined by application 1 micro sec - 10s of sec Abhinav Bhatele (CMSC498X/CMSC818X) LIVE RECORDING 8

  18. Life-cycle of a message Source Packetization and injection : delay:100s of ns Source Routers/ NIC Source Switches Source Path finding delay ~100 ns Temp storage in buffers Source Message origin points : destination, frequency, size, etc. determined by application 1 micro sec - 10s of sec Abhinav Bhatele (CMSC498X/CMSC818X) LIVE RECORDING 8

  19. Life-cycle of a message Source Packetization and injection : Links - congestion points delay:100s of ns traversal time: 1-50 ns Source Routers/ NIC Source Switches Source Path finding delay ~100 ns Temp storage in buffers Source Message origin points : destination, frequency, size, etc. determined by application 1 micro sec - 10s of sec Abhinav Bhatele (CMSC498X/CMSC818X) LIVE RECORDING 8

  20. Life-cycle of a message Source Packetization and injection : Links - congestion points delay:100s of ns traversal time: 1-50 ns Source Routers/ Routers/ Destination NIC NIC Source Switches Switches Message destination points: Source Path finding application dependent delay ~100 ns 1 micro sec - 10s of sec Temp storage in buffers Source Message origin points : destination, frequency, size, etc. determined by application 1 micro sec - 10s of sec Abhinav Bhatele (CMSC498X/CMSC818X) LIVE RECORDING 8

  21. Congestion due to network sharing • Sharing refers to network flows of different programs using the same hardware resources: links, switches • When multiple programs communicate on the network, they all suffer from congestion on shared links Abhinav Bhatele (CMSC498X/CMSC818X) LIVE RECORDING 9

  22. Congestion due to network sharing • Sharing refers to network flows of different programs using the same hardware resources: links, switches • When multiple programs communicate on the network, they all suffer from congestion on shared links Switch/router Program A Program B Abhinav Bhatele (CMSC498X/CMSC818X) LIVE RECORDING 9

  23. Congestion due to network sharing • Sharing refers to network flows of different programs using the same hardware resources: links, switches • When multiple programs communicate on the network, they all suffer from congestion on shared links Switch/router Program A Program B Abhinav Bhatele (CMSC498X/CMSC818X) LIVE RECORDING 9

  24. Congestion due to network sharing • Sharing refers to network flows of different programs using the same hardware resources: links, switches • When multiple programs communicate on the network, they all suffer from congestion on shared links Switch/router Program A Program B Abhinav Bhatele (CMSC498X/CMSC818X) LIVE RECORDING 9

  25. Congestion due to network sharing • Sharing refers to network flows of different programs using the same hardware resources: links, switches • When multiple programs communicate on the network, they all suffer from congestion on shared links Switch/router Program A Program B Abhinav Bhatele (CMSC498X/CMSC818X) LIVE RECORDING 9

  26. Congestion due to network sharing • Sharing refers to network flows of different programs using the same hardware resources: links, switches • When multiple programs communicate on the network, they all suffer from congestion on shared links Switch/router Program A Program B Abhinav Bhatele (CMSC498X/CMSC818X) LIVE RECORDING 9

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