The 26th Workshop on Sustained Simulation Performance (WSSP26) Towards Realizing a Dynamic and MPI Application-aware Interconnect with SDN Keichi Takahashi Cybermedia Center, Osaka University

The 26th Workshop on Sustained Simulation Performance (WSSP26) Introduction ‣ Why do we need an MPI Application-aware Interconnect? SDN-accelerated MPI Primitives ‣ Is our idea feasible at all? A Coordination Mechanism of Computation and Communication ‣ How do we reconfigure the interconnect in accordance with the execution of applications? A Toolset for Analyzing Application-aware Dynamic Interconnects ‣ How will the proposed architecture perform with various types of applications and clusters? Agenda 2

The 26th Workshop on Sustained Simulation Performance (WSSP26) Introduction ‣ Why do we need an MPI Application-aware Interconnect? SDN-accelerated MPI Primitives ‣ Is our idea feasible at all? A Coordination Mechanism of Computation and Communication ‣ How do we reconfigure the interconnect in accordance with the execution of applications? A Toolset for Analyzing Application-aware Dynamic Interconnects ‣ How will the proposed architecture perform with various types of applications and clusters? Agenda 2

The 26th Workshop on Sustained Simulation Performance (WSSP26) Challenges in Future Interconnects Over-provisioned designs might not scale well ‣ Interconnects can consume up to 50% of total power [1] and 1/3 of total budget of a cluster [2] ‣ Properties such as full bisection bandwidth and non-blocking may become increasingly difficult to achieve ‣ Need to improve the utilization of the interconnect Our proposal is to adopt: ‣ Dynamic (adaptive) routing ‣ Application-awareness network control 3 [1] J. Kim et al.“Flattened Butterfly : A Cost-Efficient Topology for High-Radix Networks,” ISCA, vol. 35, no. 2, pp. 126–137, 2007. [2] D. Abts et al., “Energy proportional datacenter networks,” ACM SIGARCH Comput. Archit. News, vol. 38, no. 3, p. 338, 2010.

The 26th Workshop on Sustained Simulation Performance (WSSP26) Source of Inefficiency in Current Interconnect 4

The 26th Workshop on Sustained Simulation Performance (WSSP26) Source of Inefficiency in Current Interconnect 4 Communication Pattern of Applications

The 26th Workshop on Sustained Simulation Performance (WSSP26) Source of Inefficiency in Current Interconnect 4 Communication Pattern of Applications Topology of the Interconnect

The 26th Workshop on Sustained Simulation Performance (WSSP26) Source of Inefficiency in Current Interconnect 4 Communication Pattern of Applications Topology of the Interconnect Mismatch

The 26th Workshop on Sustained Simulation Performance (WSSP26) Source of Inefficiency in Current Interconnect 4 Communication Pattern of Applications Topology of the Interconnect Mismatch

The 26th Workshop on Sustained Simulation Performance (WSSP26) Source of Inefficiency in Current Interconnect 4 Communication Pattern of Applications Topology of the Interconnect [3] S. Kamil et al. ,“Communication Requirements and Interconnect Optimization for High-End Scientific Applications,” IEEE Trans. Parallel Distrib. Syst., 2010. Lower utilization Higher congestion Lower communication performance [3] Mismatch

The 26th Workshop on Sustained Simulation Performance (WSSP26) SDN-enhanced MPI Framework Our prototype framework that integrates SDN into MPI ‣ Dynamically controls the interconnect based on the communication pattern of MPI applications ‣ Uses Software-Defined Networking (SDN) as a key technology to realize dynamic interconnect control (e.g. dynamic routing) ‣ Successfully accelerated several MPI primitives (e.g. MPI_Bcast and MPI_Allreduce) 5

The 26th Workshop on Sustained Simulation Performance (WSSP26) SDN | Software-Defined Networking 6 Feature Control Plane Data Plane Conventional Networking

The 26th Workshop on Sustained Simulation Performance (WSSP26) SDN | Software-Defined Networking 6 Feature Control Plane Data Plane Conventional Networking Disaggregation

The 26th Workshop on Sustained Simulation Performance (WSSP26) SDN | Software-Defined Networking 6 Feature Control Plane Data Plane Conventional Networking Southbound API (e.g. OpenFlow) Northbound API App App App Control Plane Data Plane Feature Software Defined Networking Disaggregation

The 26th Workshop on Sustained Simulation Performance (WSSP26) OpenFlow | Standard implementation of SDN 7 Src MAC Dst MAC … Instructions aa:aa:aa:… ff:ff:ff:… Flood bb:bb:bb:… aa:aa:aa:… Output to Port X aa:aa:aa:… bb:bb:bb:… Set Dst IP to Y,… Src MAC Dst MAC … Instructions aa:aa:aa:… ff:ff:ff:… Flood bb:bb:bb:… aa:aa:aa:… Output to Port X aa:aa:aa:… bb:bb:bb:… Set Dst IP to Y,… Src MAC Dst MAC … Instructions aa:aa:aa:… ff:ff:ff:… Flood bb:bb:bb:… aa:aa:aa:… Output to Port X aa:aa:aa:… bb:bb:bb:… Set Dst IP to Y,… Control Plane Data Plane Add/Modify/Delete flow entries Inject packets into data plane Notify flow entry misses Flow Table (Collection of flow entries) OpenFlow Controller OpenFlow Messages

The 26th Workshop on Sustained Simulation Performance (WSSP26) Basic Idea of SDN-enhanced MPI 8 Interconnect Computing Nodes 1 2 3 0 Communication Pattern 0 1 2 3 … Interconnect Control Seq.

The 26th Workshop on Sustained Simulation Performance (WSSP26) Basic Idea of SDN-enhanced MPI 8 Interconnect Computing Nodes 1 2 3 0 Communication Pattern 0 1 2 3 … Interconnect Control Seq. Extract via Tracer/Profiler
 Static Analysis

The 26th Workshop on Sustained Simulation Performance (WSSP26) Basic Idea of SDN-enhanced MPI 8 Interconnect Computing Nodes 1 2 3 0 Communication Pattern 0 1 2 3 … Interconnect Control Seq. Extract via Tracer/Profiler
 Static Analysis Resource (Path, Bandwidth, etc.) Allocation

The 26th Workshop on Sustained Simulation Performance (WSSP26) Basic Idea of SDN-enhanced MPI 8 Interconnect Computing Nodes 1 2 3 0 Communication Pattern 0 1 2 3 … Interconnect Control Seq. Proactive reconfiguration using OpenFlow Extract via Tracer/Profiler
 Static Analysis Resource (Path, Bandwidth, etc.) Allocation

The 26th Workshop on Sustained Simulation Performance (WSSP26) Related Work SDN-enhanced InfiniBand (Lee et al. SC16) ‣ Enhancement to InfiniBand that allows dynamic and per-flow level network control Conditional OpenFlow (Benito et al. HiPC 2015) ‣ Enhanced OpenFlow that allows users to add flow entries that are activated when an Ethernet Pause (IEEE 802.3x) occurs ‣ Primary goal is to implement non-minimal adaptive routing on Ethernet Quantized Congestion Notification Switch (Benito et al. HiPINEB 2017) ‣ Another enhancement to OpenFlow that uses received QCNs (802.1 Qau Quantized Congestion Notification) to probabilistically determine which path to select 9

The 26th Workshop on Sustained Simulation Performance (WSSP26) Introduction ‣ Why do we need an MPI Application-aware Interconnect? SDN-accelerated MPI Primitives ‣ Can we accelerate MPI primitives based on our idea? A Coordination Mechanism of Computation and Communication ‣ How do we reconfigure the interconnect in accordance with the execution of applications? A Toolset for Analyzing Application-aware Dynamic Interconnects ‣ How will our idea on various types of applications and clusters? Agenda 10

The 26th Workshop on Sustained Simulation Performance (WSSP26) MPI broadcast leveraging hardware-multicast ‣ Multicast rules are dynamically installed using OpenFlow ‣ Considers background traffic from other jobs to construct optimal delivery tree SDN-accelerated MPI_Bcast 11 SW1 SW2 SW3 SW4 SW5 SW6 P0 P1 P2 P3 P0 SW3 SW2 SW6 P0 P0 P0 Delivery Tree OpenFlow Ctrl.

The 26th Workshop on Sustained Simulation Performance (WSSP26) Introduction ‣ Why do we need an MPI Application-aware Interconnect? SDN-accelerated MPI Primitives ‣ Is our idea feasible at all? A Coordination Mechanism of Computation and Communication ‣ How do we reconfigure the interconnect in accordance with the execution of applications? A Toolset for Analyzing Application-aware Dynamic Interconnects ‣ How will our idea on various types of applications and clusters? Agenda 12

The 26th Workshop on Sustained Simulation Performance (WSSP26) Introduction ‣ Why do we need an MPI Application-aware Interconnect? SDN-accelerated MPI Primitives ‣ Is our idea feasible at all? A Coordination Mechanism of Computation and Communication ‣ How do we reconfigure the interconnect in accordance with the execution of applications? A Toolset for Analyzing Application-aware Dynamic Interconnects ‣ How will our idea on various types of applications and clusters? Agenda 12

The 26th Workshop on Sustained Simulation Performance (WSSP26) Synchronizing Computation and Communication 13 #include int main() { MPI_Init(&argc, &argv); MPI_Bcast(buf, count, …); /* … */ MPI_Allreduce(buf, count, …); MPI_Finalize(); } Src MAC Dst MAC … Instructions aa:aa:aa:… ff:ff:ff:… Flood bb:bb:bb:… aa:aa:aa:… Output to Port X aa:aa:aa:… bb:bb:bb:… Set Dst IP to Y,… Time-varying Communication Pattern Reconfiguration of the Interconnect How do we synchronize these two? Execution

The 26th Workshop on Sustained Simulation Performance (WSSP26) Our Idea: Embed encoded MPI envelope into each packet ‣ Current implementation uses virtual MAC addresses to represent tags UnisonFlow 14 MPI Packet Tag Custom Kernel Module Kernel Space User Space MPI Library MPI Application ioctl MPI Packet Tag Instructions A Output to port X B Output to port Y … … MPI MPI Packet Tag Embed Packet Flow Controlled
 Based on Tag Value MPI Envelope: Rank, Primitive Type,
 Communicator, etc. [5] Keichi Takahashi, "Concept and Design of SDN-enhanced MPI Framework", EWSDN 2015

The 26th Workshop on Sustained Simulation Performance (WSSP26) Introduction ‣ Why do we need an MPI Application-aware Interconnect? SDN-accelerated MPI Primitives ‣ Is our idea feasible at all? A Coordination Mechanism of Computation and Communication ‣ How do we reconfigure the interconnect in accordance with the execution of applications? A Toolset for Analyzing Application-aware Dynamic Interconnects ‣ How will our idea on various types of applications and clusters? Agenda 15

The 26th Workshop on Sustained Simulation Performance (WSSP26) Introduction ‣ Why do we need an MPI Application-aware Interconnect? SDN-accelerated MPI Primitives ‣ Is our idea feasible at all? A Coordination Mechanism of Computation and Communication ‣ How do we reconfigure the interconnect in accordance with the execution of applications? A Toolset for Analyzing Application-aware Dynamic Interconnects ‣ How will our idea on various types of applications and clusters? Agenda 15

The 26th Workshop on Sustained Simulation Performance (WSSP26) Need for a Holistic Analysis in SDN-enhanced MPI 16 Job Queue j1 j2 j3 j4

The 26th Workshop on Sustained Simulation Performance (WSSP26) Need for a Holistic Analysis in SDN-enhanced MPI 16 Job Queue j1 j2 j3 j4

The 26th Workshop on Sustained Simulation Performance (WSSP26) Need for a Holistic Analysis in SDN-enhanced MPI 16 Job Queue j1 j2 j3 j4 Job Scheduling

The 26th Workshop on Sustained Simulation Performance (WSSP26) Need for a Holistic Analysis in SDN-enhanced MPI 16 2 4 5 1 0 3 Job Queue j1 j2 j3 j4 Job Scheduling

The 26th Workshop on Sustained Simulation Performance (WSSP26) Need for a Holistic Analysis in SDN-enhanced MPI 16 2 4 5 1 0 3 Job Queue j1 j2 j3 j4 Communication Pattern Job Scheduling

The 26th Workshop on Sustained Simulation Performance (WSSP26) Need for a Holistic Analysis in SDN-enhanced MPI 16 2 4 5 1 0 3 Job Queue j1 j2 j3 j4 Communication Pattern Job Scheduling

The 26th Workshop on Sustained Simulation Performance (WSSP26) Need for a Holistic Analysis in SDN-enhanced MPI 16 2 4 5 1 0 3 Job Queue j1 j2 j3 j4 Communication Pattern Job Scheduling Node Selection

The 26th Workshop on Sustained Simulation Performance (WSSP26) PEs PEs PEs Need for a Holistic Analysis in SDN-enhanced MPI 16 2 4 5 1 0 3 Job Queue j1 j2 j3 j4 Communication Pattern Job Scheduling Node Selection

The 26th Workshop on Sustained Simulation Performance (WSSP26) PEs PEs PEs Need for a Holistic Analysis in SDN-enhanced MPI 16 0 1 2 3 4 5 2 4 5 1 0 3 Job Queue j1 j2 j3 j4 Communication Pattern Job Scheduling Node Selection

The 26th Workshop on Sustained Simulation Performance (WSSP26) PEs PEs PEs Need for a Holistic Analysis in SDN-enhanced MPI 16 0 1 2 3 4 5 2 4 5 1 0 3 Job Queue j1 j2 j3 j4 Communication Pattern Job Scheduling Node Selection Process Mapping

The 26th Workshop on Sustained Simulation Performance (WSSP26) PEs PEs PEs Need for a Holistic Analysis in SDN-enhanced MPI 16 0 1 2 3 4 5 2 4 5 1 0 3 Job Queue j1 j2 j3 j4 Communication Pattern Job Scheduling Node Selection Process Mapping

The 26th Workshop on Sustained Simulation Performance (WSSP26) PEs PEs PEs Need for a Holistic Analysis in SDN-enhanced MPI 16 0 1 2 3 4 5 2 4 5 1 0 3 Job Queue j1 j2 j3 j4 Communication Pattern Job Scheduling Node Selection Process Mapping

The 26th Workshop on Sustained Simulation Performance (WSSP26) PEs PEs PEs Need for a Holistic Analysis in SDN-enhanced MPI 16 0 1 2 3 4 5 2 4 5 1 0 3 Job Queue j1 j2 j3 j4 Communication Pattern Job Scheduling Node Selection Process Mapping

The 26th Workshop on Sustained Simulation Performance (WSSP26) PEs PEs PEs Need for a Holistic Analysis in SDN-enhanced MPI 16 0 1 2 3 4 5 2 4 5 1 0 3 Job Queue j1 j2 j3 j4 Communication Pattern Job Scheduling Node Selection Process Mapping Routing

The 26th Workshop on Sustained Simulation Performance (WSSP26) Q1: Impact of the Communication Pattern How does the traffic load in the interconnect change for diverse applications? ‣ What kind of application benefits most from SDN-enhanced MPI? ‣ What happens if the number of processes scales out? 17

The 26th Workshop on Sustained Simulation Performance (WSSP26) Q2: Impact of the Cluster Configuration How does the traffic load in the interconnect change under diverse clusters with different configurations? ‣ How do job scheduling, node selection and process mapping affect the performance of applications? ‣ How does the topology of the interconnect impact the performance? ‣ What happens if the size of cluster scales out? 18 0 Node Selection (i.e. which node should be allocated to a given job?) Process Placement (i.e. which node should execute a process?) j1 j2 j3 j4 1 2 3 Job Scheduling (i.e. which job should be executed next?)

The 26th Workshop on Sustained Simulation Performance (WSSP26) We aim to develop a toolset to help answer these questions ‣ How does the traffic load in the interconnect change for diverse applications? ‣ How does the traffic load in the interconnect change under diverse clusters with different configurations? Simulator-based approach is taken to allow rapid assessment ‣ Requirements for the toolset are summarized as: Requirements for the Interconnect Analysis Toolset 19 1. Support for application-aware dynamic routing 2. Support for communication patterns of real-world applications 3. Support for diverse cluster configurations

The 26th Workshop on Sustained Simulation Performance (WSSP26) PFProf (profiler) and PFSim (simulator) constitute PFAnalyzer [6] ‣ PFProf - Fine-grained MPI profiler for observing network activity caused by MPI function calls (Requirement 2) ‣ PFSim - Lightweight simulator to simulate traffic load in the interconnect targeting application-aware dynamic interconnects
 (Requirement 1, 2, 3) Overview of PFAnalyzer 20 PFSim PFProf Application Profile Result [6] Keichi Takahashi et al., "A Toolset for Analyzing Application-aware Dynamic Interconnects", HPCMASPA 2017

The 26th Workshop on Sustained Simulation Performance (WSSP26) PFProf: Motivation Existing profilers do not capture the underlying pt2pt communication of collective communication ‣ They are designed to support code tuning and optimization, not network traffic analysis. ‣ MPI Profiling Interface (PMPI) only captures individual MPI function calls. 21 1 2 3 4 5 6 7 1 4 3 2 5 7 6 Actual communication performed 0 0 Behavior of MPI_Bcast as seen from applications 21

The 26th Workshop on Sustained Simulation Performance (WSSP26) PFProf: Implementation MPI Performance Revealing Extension Interface (PERUSE) is utilized ‣ PERUSE exposes internal information of MPI library ‣ Notifies you when a request is posted/completed, a transfer begins/ends, etc. 22 PFProf MPI Application MPI Library • MPI_Init • MPI_Finalize • MPI_Comm_create • MPI_Comm_dup • MPI_Comm_free

The 26th Workshop on Sustained Simulation Performance (WSSP26) PFProf: Implementation MPI Performance Revealing Extension Interface (PERUSE) is utilized ‣ PERUSE exposes internal information of MPI library ‣ Notifies you when a request is posted/completed, a transfer begins/ends, etc. 22 PFProf MPI Application MPI Library • MPI_Init • MPI_Finalize • MPI_Comm_create • MPI_Comm_dup • MPI_Comm_free Subscribe to PERUSE Events

The 26th Workshop on Sustained Simulation Performance (WSSP26) PFProf: Implementation MPI Performance Revealing Extension Interface (PERUSE) is utilized ‣ PERUSE exposes internal information of MPI library ‣ Notifies you when a request is posted/completed, a transfer begins/ends, etc. 22 PFProf MPI Application MPI Library • MPI_Init • MPI_Finalize • MPI_Comm_create • MPI_Comm_dup • MPI_Comm_free Call MPI Functions Subscribe to PERUSE Events

The 26th Workshop on Sustained Simulation Performance (WSSP26) PFProf: Implementation MPI Performance Revealing Extension Interface (PERUSE) is utilized ‣ PERUSE exposes internal information of MPI library ‣ Notifies you when a request is posted/completed, a transfer begins/ends, etc. 22 PFProf MPI Application MPI Library • MPI_Init • MPI_Finalize • MPI_Comm_create • MPI_Comm_dup • MPI_Comm_free Call MPI Functions Notify PERUSE Events Subscribe to PERUSE Events

The 26th Workshop on Sustained Simulation Performance (WSSP26) PFProf: Implementation MPI Performance Revealing Extension Interface (PERUSE) is utilized ‣ PERUSE exposes internal information of MPI library ‣ Notifies you when a request is posted/completed, a transfer begins/ends, etc. 22 PFProf MPI Application MPI Library • MPI_Init • MPI_Finalize • MPI_Comm_create • MPI_Comm_dup • MPI_Comm_free Call MPI Functions Notify PERUSE Events Subscribe to PERUSE Events Hook MPI Functions with PMPI

The 26th Workshop on Sustained Simulation Performance (WSSP26) Representation of Communication Pattern ‣ Defined as a matrix T of which element Tij is equal to the volume of traffic sent from rank i to rank j ‣ Implies that the volume of traffic between processes as constant during the execution of a job 23 0 50 100 Sender Rank 0 25 50 75 100 125 Receiver Rank 0.0 0.2 0.4 0.6 0.8 1.0 Sent Bytes ⇥108 An example obtained from running the NERSC MILC benchmark with 128 processes The communication pattern of an application is represented using its traffic matrix

The 26th Workshop on Sustained Simulation Performance (WSSP26) PFProf: Overhead Evaluation 24 101 103 105 107 Message Size [B] 0.0 0.2 0.4 0.6 0.8 1.0 Relative Throughput 100 101 102 Throughput [MB/s] w/o profiler w/ profiler 101 103 105 107 Message Size [B] 0.0 0.2 0.4 0.6 0.8 1.0 1.2 Relative Latency 102 103 104 Latency [µs] w/o profiler w/ profiler Throughput (osu_bw) Latency (osu_latency) Measured throughput and latency of pt2pt communication with and without PFProf using the OSU Microbenchmark

The 26th Workshop on Sustained Simulation Performance (WSSP26) PFSim: Overview 25 PFSim Interconnect
 Usage Performance
 Metric Plot Simulation
 Log Output Simulation
 Scenario Cluster
 Configuration Communication
 Patterns Input Scheduling Plugin Node Selection Process Placement Routing PFProf Cluster
 Topology

The 26th Workshop on Sustained Simulation Performance (WSSP26) PFSim: Overview 25 PFSim Interconnect
 Usage Performance
 Metric Plot Simulation
 Log Output Simulation
 Scenario Cluster
 Configuration Communication
 Patterns Input Scheduling Plugin Node Selection Process Placement Routing PFProf Cluster
 Topology For Requirement 2

The 26th Workshop on Sustained Simulation Performance (WSSP26) PFSim: Overview 25 PFSim Interconnect
 Usage Performance
 Metric Plot Simulation
 Log Output Simulation
 Scenario Cluster
 Configuration Communication
 Patterns Input Scheduling Plugin Node Selection Process Placement Routing PFProf For Requirement 3 For Requirement 3 Cluster
 Topology For Requirement 2

The 26th Workshop on Sustained Simulation Performance (WSSP26) PFSim: Overview 25 PFSim Interconnect
 Usage Performance
 Metric Plot Simulation
 Log Output Simulation
 Scenario Cluster
 Configuration Communication
 Patterns Input Scheduling Plugin Node Selection Process Placement Routing PFProf For Requirement 3 For Requirement 1 For Requirement 3 Cluster
 Topology For Requirement 2

The 26th Workshop on Sustained Simulation Performance (WSSP26) PFSim: Architecture 26 Event Event Event Queue j1 j2 j3 j4 Job Submitted Event Handlers … Job Started Job Finished Job Queue Simulator State Update Interconnect Computing Nodes Event Dispatch

The 26th Workshop on Sustained Simulation Performance (WSSP26) PFSim: Architecture 26 Event Event Event Queue j1 j2 j3 j4 Job Submitted Event Handlers … Job Started Job Finished Job Queue Simulator State Update Interconnect Computing Nodes Event Dispatch Customized via Plugins

The 26th Workshop on Sustained Simulation Performance (WSSP26) PFSim: Example Input & Output 27 topology: topologies/milk.graphml output: output/milk-cg-dmodk algorithms: scheduler: - pfsim.scheduler.FCFSScheduler node_selector: - pfsim.node_selector.LinearNodeSelector - pfsim.node_selector.RandomNodeSelector process_mapper: - pfsim.process_mapper.LinearProcessMapper - pfsim.process_mapper.CyclicProcessMapper router: - pfsim.router.DmodKRouter - pfsim.router.GreedyRouter - pfsim.router.GreedyRouter2 jobs: - submit: distribution: pfsim.math.ExponentialDistribution params: lambd: 0.1 trace: traces/cg-c-128.tar.gz Cluster Configuration (YAML) Interconnect Utilization
 (Output GraphML visualized with Cytoscape)

The 26th Workshop on Sustained Simulation Performance (WSSP26) PFSim: Example Input & Output 27 topology: topologies/milk.graphml output: output/milk-cg-dmodk algorithms: scheduler: - pfsim.scheduler.FCFSScheduler node_selector: - pfsim.node_selector.LinearNodeSelector - pfsim.node_selector.RandomNodeSelector process_mapper: - pfsim.process_mapper.LinearProcessMapper - pfsim.process_mapper.CyclicProcessMapper router: - pfsim.router.DmodKRouter - pfsim.router.GreedyRouter - pfsim.router.GreedyRouter2 jobs: - submit: distribution: pfsim.math.ExponentialDistribution params: lambd: 0.1 trace: traces/cg-c-128.tar.gz Cluster Configuration (YAML) Interconnect Utilization
 (Output GraphML visualized with Cytoscape) High Traffic Load

The 26th Workshop on Sustained Simulation Performance (WSSP26) PFSim: Example Input & Output 27 topology: topologies/milk.graphml output: output/milk-cg-dmodk algorithms: scheduler: - pfsim.scheduler.FCFSScheduler node_selector: - pfsim.node_selector.LinearNodeSelector - pfsim.node_selector.RandomNodeSelector process_mapper: - pfsim.process_mapper.LinearProcessMapper - pfsim.process_mapper.CyclicProcessMapper router: - pfsim.router.DmodKRouter - pfsim.router.GreedyRouter - pfsim.router.GreedyRouter2 jobs: - submit: distribution: pfsim.math.ExponentialDistribution params: lambd: 0.1 trace: traces/cg-c-128.tar.gz Cluster Configuration (YAML) Interconnect Utilization
 (Output GraphML visualized with Cytoscape) High Traffic Load Less Traffic Load

Simulated Configurations 28 Node Selection Process Placement Routing Linear Random Linear Cyclic D-mod-K Dynamic 0 1 2 3 4 5 0 3 1 4 2 5 Path selected solely based on the destination of flow 0 50 100 Sender Rank 0 25 50 75 100 125 Receiver Rank 0.0 0.2 0.4 0.6 0.8 1.0 Sent Bytes ⇥108 Path allocated based on communication pattern (heavy pairs first)

Simulation Results Maximum traffic load on all links is plotted as a performance indicator 29 Linear/Block/DmodK Linear/Block/Dynamic Linear/Cyclic/DmodK Linear/Cyclic/Dynamic Random/Block/DmodK Random/Block/Dynamic Random/Cyclic/DmodK Random/Cyclic/Dynamic 0.0 0.5 1.0 1.5 2.0 2.5 Maximum Tra c (Normalized) Linear/Block/DmodK Linear/Block/Dynamic Linear/Cyclic/DmodK Linear/Cyclic/Dynamic Random/Block/DmodK Random/Block/Dynamic Random/Cyclic/DmodK Random/Cyclic/Dynamic 0.00 0.25 0.50 0.75 1.00 1.25 1.50 Maximum Tra c (Normalized) NAS CG Benchmark (128 ranks) NERC MILC Benchmark (128 ranks) D-mod-K Dynamic

The 26th Workshop on Sustained Simulation Performance (WSSP26) Further Challenges Simulation-based study of large-scale clusters with different topologies ‣ Currently, our institution owns only a small-scale experimental cluster
 employed with SDN Integrate interconnect controller with scheduler and MPI runtime ‣ To support multiple jobs running in parallel ‣ To investigate the effect of node allocation and process placement Better application-aware routing algorithms ‣ Currently, a simple greedy like algorithm is used ‣ How about optimization or machine learning? 30

The 26th Workshop on Sustained Simulation Performance (WSSP26) Summary Current static and over-provisioned interconnects might not scale well ‣ SDN allows us to build a more dynamic and application-aware interconnects ‣ Such architecture could improve the utilization of the interconnect and communication performance Our achievements so far include: ‣ SDN-accelerated MPI primitives such as Bcast and Allreduce ‣ UnisonFlow, a coordination mechanism of computation and communication ‣ PFAnalyzer, a toolset for analyzing application-aware dynamic interconnects 31