Exploring Use-cases for Non-Volatile Memories in support of HPC Resilience
|
|
- Wilfred Robbins
- 5 years ago
- Views:
Transcription
1 Exploring Use-cases for Non-Volatile Memories in support of HPC Resilience Onkar Patil 1, Saurabh Hukerikar 2, Frank Mueller 1, Christian Engelmann 2 1 Dept. of Computer Science, North Carolina State University 2 Computer Science and Mathematics Division, Oak Ridge National Laboratory
2 MOTIVATION Exaflop Computers compute devices + memory devices + interconnects + cooling and power Close Proximity! Manufacturing processes not foolproof Lower durability and reliability Frequency of device failures and data corruptions effectiveness and utility Future Applications need to be more resilient, Maintain a balance between performance and power consumption Minimize trade-offs
3 PROBLEM STATEMENT Non-volatile memory (NVM) technologies maintain state of computation in the primary memory architecture More potential as specialized hardware Data Retention critical in improving resilience of an application against crashes Persistent memory regions to improve HPC resiliency key aspect of this project APPLICATION APPLICATION APPLICATION STATIC DATA STRUCTURES DYNAMIC DATA STRUCTURES STATIC DATA STRUCTURES DYNAMIC DATA STRUCTURES STATIC DATA STRUCTURES DYNAMIC DATA STRUCTURES NVM NVM NVM NVM-based Main Memory Application-directed Checkpointing Data Versioning
4 RESULTS Experimentation Setup 16-node cluster with Dual socket, Quad-Core AMD Opteron, 128 GB memory, Intel SSD from 100GB to 256GB DGEMM benchmark of the HPCC benchmark suite Tested for 4, 8 and 16-node configurations for a matrix sizes of 1000, 2000 and 3000 elements
5 GFLOPS Time(sec) 10 GFLOPS in node scaling for StarDGEMM PMEM_ONLY PMEM_CPY PMEM_VER 100 Execution times in node scaling for StarDGEMM PMEM_ONLY PMEM_CPY 1 10 PMEM_VER Nodes Nodes 8 16 only allocation and NVM-based main memory perform better An inefficient lookup algorithm
6 GFLOPS Time(sec) 10 1 GFLOPS for problem size scaling in StarDGEMM PMEM_ONL Y Execution time for problem size scaling in StarDGEMM PMEM_ONLY PMEM_CPY PMEM_VER No. of elements All modes perform similar and consistently for node and data scaling Execution time increases exponentially for multiple copies of memory No. of elements
7 CONCLUSION & FUTURE WORK Conclusion: Non-volatile memory devices can be used as specialized hardware for improving the resilience of the system Future Work: Memory usage modes to make applications efficient and maintain complete system state Minimal overhead Support more complex applications Lightweight recovery mechanisms to work with the checkpointing schemes Reduce downtime and rollback time Intelligent policies that can help build resilient static and dynamic runtime system
8 Evaluating Performance of Burst Buffer Models for Real-Application Workloads in HPC Systems Harsh Khetawat Frank Mueller Christopher Zimmer
9 Introduction Existing storage systems becoming bottleneck Solution: burst buffers Use burst buffers for: Checkpoint/Restart I/O Staging Write-through cache for parallel FS Burst Buffers on Cori
10 Burst buffer placement: Placement Co-located with compute nodes (Summit) Co-located with I/O nodes (Cori) Separate set of nodes Trade-offs in choice of placements Capability I/O models, staging, etc. Predictability Impact on shared resources, runtime variability Economic Infrastructure reuse, cost of storage device I/O performance dependent on placement Choice of network topology
11 Idea Simulate network and burst buffer architectures CODES simulation suite Real-world I/O traces (Darshan) Full multi-tenant system with mixed workloads (capability/capacity) Supports network topologies Local & external storage models Combine network topologies and storage architectures Performance under striping/protection schemes Reproducible tool for HPC centers
12 Conclusion Determine based on workload characteristics: Burst buffer placement Network topology Performance of striping across burst buffers Overhead of resilience schemes Reproducible tool to: Simulate specific workloads Determine best fit
13 Thank You
Scalable, Fault-Tolerant Membership for MPI Tasks on HPC Systems
fastos.org/molar Scalable, Fault-Tolerant Membership for MPI Tasks on HPC Systems Jyothish Varma 1, Chao Wang 1, Frank Mueller 1, Christian Engelmann, Stephen L. Scott 1 North Carolina State University,
More informationCombing Partial Redundancy and Checkpointing for HPC
Combing Partial Redundancy and Checkpointing for HPC James Elliott, Kishor Kharbas, David Fiala, Frank Mueller, Kurt Ferreira, and Christian Engelmann North Carolina State University Sandia National Laboratory
More informationFunctional Partitioning to Optimize End-to-End Performance on Many-core Architectures
Functional Partitioning to Optimize End-to-End Performance on Many-core Architectures Min Li, Sudharshan S. Vazhkudai, Ali R. Butt, Fei Meng, Xiaosong Ma, Youngjae Kim,Christian Engelmann, and Galen Shipman
More informationResilience Design Patterns: A Structured Approach to Resilience at Extreme Scale
Resilience Design Patterns: A Structured Approach to Resilience at Extreme Scale Saurabh Hukerikar Christian Engelmann Computer Science Research Group Computer Science & Mathematics Division Oak Ridge
More informationREMEM: REmote MEMory as Checkpointing Storage
REMEM: REmote MEMory as Checkpointing Storage Hui Jin Illinois Institute of Technology Xian-He Sun Illinois Institute of Technology Yong Chen Oak Ridge National Laboratory Tao Ke Illinois Institute of
More informationAggregation of Real-Time System Monitoring Data for Analyzing Large-Scale Parallel and Distributed Computing Environments
Aggregation of Real-Time System Monitoring Data for Analyzing Large-Scale Parallel and Distributed Computing Environments Swen Böhm 1,2, Christian Engelmann 2, and Stephen L. Scott 2 1 Department of Computer
More informationBzTree: A High-Performance Latch-free Range Index for Non-Volatile Memory
BzTree: A High-Performance Latch-free Range Index for Non-Volatile Memory JOY ARULRAJ JUSTIN LEVANDOSKI UMAR FAROOQ MINHAS PER-AKE LARSON Microsoft Research NON-VOLATILE MEMORY [NVM] PERFORMANCE DRAM VOLATILE
More informationA2E: Adaptively Aggressive Energy Efficient DVFS Scheduling for Data Intensive Applications
A2E: Adaptively Aggressive Energy Efficient DVFS Scheduling for Data Intensive Applications Li Tan 1, Zizhong Chen 1, Ziliang Zong 2, Rong Ge 3, and Dong Li 4 1 University of California, Riverside 2 Texas
More informationData Partitioning on Heterogeneous Multicore and Multi-GPU systems Using Functional Performance Models of Data-Parallel Applictions
Data Partitioning on Heterogeneous Multicore and Multi-GPU systems Using Functional Performance Models of Data-Parallel Applictions Ziming Zhong Vladimir Rychkov Alexey Lastovetsky Heterogeneous Computing
More informationPhilip C. Roth. Computer Science and Mathematics Division Oak Ridge National Laboratory
Philip C. Roth Computer Science and Mathematics Division Oak Ridge National Laboratory A Tree-Based Overlay Network (TBON) like MRNet provides scalable infrastructure for tools and applications MRNet's
More informationScalable and Fault Tolerant Failure Detection and Consensus
EuroMPI'15, Bordeaux, France, September 21-23, 2015 Scalable and Fault Tolerant Failure Detection and Consensus Amogh Katti, Giuseppe Di Fatta, University of Reading, UK Thomas Naughton, Christian Engelmann
More informationProactive Process-Level Live Migration in HPC Environments
Proactive Process-Level Live Migration in HPC Environments Chao Wang, Frank Mueller North Carolina State University Christian Engelmann, Stephen L. Scott Oak Ridge National Laboratory SC 08 Nov. 20 Austin,
More informationlibhio: Optimizing IO on Cray XC Systems With DataWarp
libhio: Optimizing IO on Cray XC Systems With DataWarp May 9, 2017 Nathan Hjelm Cray Users Group May 9, 2017 Los Alamos National Laboratory LA-UR-17-23841 5/8/2017 1 Outline Background HIO Design Functionality
More informationTechniques to improve the scalability of Checkpoint-Restart
Techniques to improve the scalability of Checkpoint-Restart Bogdan Nicolae Exascale Systems Group IBM Research Ireland 1 Outline A few words about the lab and team Challenges of Exascale A case for Checkpoint-Restart
More informationSTORAGE LATENCY x. RAMAC 350 (600 ms) NAND SSD (60 us)
1 STORAGE LATENCY 2 RAMAC 350 (600 ms) 1956 10 5 x NAND SSD (60 us) 2016 COMPUTE LATENCY 3 RAMAC 305 (100 Hz) 1956 10 8 x 1000x CORE I7 (1 GHZ) 2016 NON-VOLATILE MEMORY 1000x faster than NAND 3D XPOINT
More informationAutomatic Identification of Application I/O Signatures from Noisy Server-Side Traces. Yang Liu Raghul Gunasekaran Xiaosong Ma Sudharshan S.
Automatic Identification of Application I/O Signatures from Noisy Server-Side Traces Yang Liu Raghul Gunasekaran Xiaosong Ma Sudharshan S. Vazhkudai Instance of Large-Scale HPC Systems ORNL s TITAN (World
More informationUsing Transparent Compression to Improve SSD-based I/O Caches
Using Transparent Compression to Improve SSD-based I/O Caches Thanos Makatos, Yannis Klonatos, Manolis Marazakis, Michail D. Flouris, and Angelos Bilas {mcatos,klonatos,maraz,flouris,bilas}@ics.forth.gr
More informationPreparing GPU-Accelerated Applications for the Summit Supercomputer
Preparing GPU-Accelerated Applications for the Summit Supercomputer Fernanda Foertter HPC User Assistance Group Training Lead foertterfs@ornl.gov This research used resources of the Oak Ridge Leadership
More informationMunara Tolubaeva Technical Consulting Engineer. 3D XPoint is a trademark of Intel Corporation in the U.S. and/or other countries.
Munara Tolubaeva Technical Consulting Engineer 3D XPoint is a trademark of Intel Corporation in the U.S. and/or other countries. notices and disclaimers Intel technologies features and benefits depend
More informationHP-DAEMON: High Performance Distributed Adaptive Energy-efficient Matrix-multiplicatiON
HP-DAEMON: High Performance Distributed Adaptive Energy-efficient Matrix-multiplicatiON Li Tan 1, Longxiang Chen 1, Zizhong Chen 1, Ziliang Zong 2, Rong Ge 3, and Dong Li 4 1 University of California,
More informationQuantifying power consumption variations of HPC systems using SPEC MPI benchmarks
Center for Information Services and High Performance Computing (ZIH) Quantifying power consumption variations of HPC systems using SPEC MPI benchmarks EnA-HPC, Sept 16 th 2010, Robert Schöne, Daniel Molka,
More informationAccelerating Microsoft SQL Server Performance With NVDIMM-N on Dell EMC PowerEdge R740
Accelerating Microsoft SQL Server Performance With NVDIMM-N on Dell EMC PowerEdge R740 A performance study with NVDIMM-N Dell EMC Engineering September 2017 A Dell EMC document category Revisions Date
More informationAccurate emulation of CPU performance
Accurate emulation of CPU performance Tomasz Buchert 1 Lucas Nussbaum 2 Jens Gustedt 1 1 INRIA Nancy Grand Est 2 LORIA / Nancy - Université Validation of distributed systems Approaches: Theoretical approach
More informationScalaIOTrace: Scalable I/O Tracing and Analysis
ScalaIOTrace: Scalable I/O Tracing and Analysis Karthik Vijayakumar 1, Frank Mueller 1, Xiaosong Ma 1,2, Philip C. Roth 2 1 Department of Computer Science, NCSU 2 Computer Science and Mathematics Division,
More informationPerformance and Energy Usage of Workloads on KNL and Haswell Architectures
Performance and Energy Usage of Workloads on KNL and Haswell Architectures Tyler Allen 1 Christopher Daley 2 Doug Doerfler 2 Brian Austin 2 Nicholas Wright 2 1 Clemson University 2 National Energy Research
More informationThe Fusion Distributed File System
Slide 1 / 44 The Fusion Distributed File System Dongfang Zhao February 2015 Slide 2 / 44 Outline Introduction FusionFS System Architecture Metadata Management Data Movement Implementation Details Unique
More informationConsolidating Complementary VMs with Spatial/Temporalawareness
Consolidating Complementary VMs with Spatial/Temporalawareness in Cloud Datacenters Liuhua Chen and Haiying Shen Dept. of Electrical and Computer Engineering Clemson University, SC, USA 1 Outline Introduction
More informationxsim The Extreme-Scale Simulator
www.bsc.es xsim The Extreme-Scale Simulator Janko Strassburg Severo Ochoa Seminar @ BSC, 28 Feb 2014 Motivation Future exascale systems are predicted to have hundreds of thousands of nodes, thousands of
More informationA Case for High Performance Computing with Virtual Machines
A Case for High Performance Computing with Virtual Machines Wei Huang*, Jiuxing Liu +, Bulent Abali +, and Dhabaleswar K. Panda* *The Ohio State University +IBM T. J. Waston Research Center Presentation
More informationAccelerating Real-Time Big Data. Breaking the limitations of captive NVMe storage
Accelerating Real-Time Big Data Breaking the limitations of captive NVMe storage 18M IOPs in 2u Agenda Everything related to storage is changing! The 3rd Platform NVM Express architected for solid state
More informationBig and Fast. Anti-Caching in OLTP Systems. Justin DeBrabant
Big and Fast Anti-Caching in OLTP Systems Justin DeBrabant Online Transaction Processing transaction-oriented small footprint write-intensive 2 A bit of history 3 OLTP Through the Years relational model
More informationThe Oracle Database Appliance I/O and Performance Architecture
Simple Reliable Affordable The Oracle Database Appliance I/O and Performance Architecture Tammy Bednar, Sr. Principal Product Manager, ODA 1 Copyright 2012, Oracle and/or its affiliates. All rights reserved.
More informationAdaptive Power Profiling for Many-Core HPC Architectures
Adaptive Power Profiling for Many-Core HPC Architectures Jaimie Kelley, Christopher Stewart The Ohio State University Devesh Tiwari, Saurabh Gupta Oak Ridge National Laboratory State-of-the-Art Schedulers
More informationPerformance of Mellanox ConnectX Adapter on Multi-core Architectures Using InfiniBand. Abstract
Performance of Mellanox ConnectX Adapter on Multi-core Architectures Using InfiniBand Abstract...1 Introduction...2 Overview of ConnectX Architecture...2 Performance Results...3 Acknowledgments...7 For
More informationPHX: Memory Speed HPC I/O with NVM. Pradeep Fernando Sudarsun Kannan, Ada Gavrilovska, Karsten Schwan
PHX: Memory Speed HPC I/O with NVM Pradeep Fernando Sudarsun Kannan, Ada Gavrilovska, Karsten Schwan Node Local Persistent I/O? Node local checkpoint/ restart - Recover from transient failures ( node restart)
More informationHigh-Performance Key-Value Store on OpenSHMEM
High-Performance Key-Value Store on OpenSHMEM Huansong Fu*, Manjunath Gorentla Venkata, Ahana Roy Choudhury*, Neena Imam, Weikuan Yu* *Florida State University Oak Ridge National Laboratory Outline Background
More informationPortable SHMEMCache: A High-Performance Key-Value Store on OpenSHMEM and MPI
Portable SHMEMCache: A High-Performance Key-Value Store on OpenSHMEM and MPI Huansong Fu*, Manjunath Gorentla Venkata, Neena Imam, Weikuan Yu* *Florida State University Oak Ridge National Laboratory Outline
More informationDell Fluid Data solutions. Powerful self-optimized enterprise storage. Dell Compellent Storage Center: Designed for business results
Dell Fluid Data solutions Powerful self-optimized enterprise storage Dell Compellent Storage Center: Designed for business results The Dell difference: Efficiency designed to drive down your total cost
More informationCray XD1 Supercomputer Release 1.3 CRAY XD1 DATASHEET
CRAY XD1 DATASHEET Cray XD1 Supercomputer Release 1.3 Purpose-built for HPC delivers exceptional application performance Affordable power designed for a broad range of HPC workloads and budgets Linux,
More informationMoneta: A High-Performance Storage Architecture for Next-generation, Non-volatile Memories
Moneta: A High-Performance Storage Architecture for Next-generation, Non-volatile Memories Adrian M. Caulfield Arup De, Joel Coburn, Todor I. Mollov, Rajesh K. Gupta, Steven Swanson Non-Volatile Systems
More informationHeckaton. SQL Server's Memory Optimized OLTP Engine
Heckaton SQL Server's Memory Optimized OLTP Engine Agenda Introduction to Hekaton Design Consideration High Level Architecture Storage and Indexing Query Processing Transaction Management Transaction Durability
More informationA PCIe Congestion-Aware Performance Model for Densely Populated Accelerator Servers
A PCIe Congestion-Aware Performance Model for Densely Populated Accelerator Servers Maxime Martinasso, Grzegorz Kwasniewski, Sadaf R. Alam, Thomas C. Schulthess, Torsten Hoefler Swiss National Supercomputing
More informationNERSC Site Update. National Energy Research Scientific Computing Center Lawrence Berkeley National Laboratory. Richard Gerber
NERSC Site Update National Energy Research Scientific Computing Center Lawrence Berkeley National Laboratory Richard Gerber NERSC Senior Science Advisor High Performance Computing Department Head Cori
More informationSingle-Points of Performance
Single-Points of Performance Mellanox Technologies Inc. 29 Stender Way, Santa Clara, CA 9554 Tel: 48-97-34 Fax: 48-97-343 http://www.mellanox.com High-performance computations are rapidly becoming a critical
More informationDISP: Optimizations Towards Scalable MPI Startup
DISP: Optimizations Towards Scalable MPI Startup Huansong Fu, Swaroop Pophale*, Manjunath Gorentla Venkata*, Weikuan Yu Florida State University *Oak Ridge National Laboratory Outline Background and motivation
More informationSOLVING THE DRAM SCALING CHALLENGE: RETHINKING THE INTERFACE BETWEEN CIRCUITS, ARCHITECTURE, AND SYSTEMS
SOLVING THE DRAM SCALING CHALLENGE: RETHINKING THE INTERFACE BETWEEN CIRCUITS, ARCHITECTURE, AND SYSTEMS Samira Khan MEMORY IN TODAY S SYSTEM Processor DRAM Memory Storage DRAM is critical for performance
More informationUniversal Storage. Innovation to Break Decades of Tradeoffs VASTDATA.COM
Universal Storage Innovation to Break Decades of Tradeoffs F e b r u a r y 2 0 1 9 AN END TO DECADES OF STORAGE COMPLEXITY AND COMPROMISE SUMMARY When it s possible to store all of your data in a single
More informationSix-Core AMD Opteron Processor
What s you should know about the Six-Core AMD Opteron Processor (Codenamed Istanbul ) Six-Core AMD Opteron Processor Versatility Six-Core Opteron processors offer an optimal mix of performance, energy
More informationScalable In-memory Checkpoint with Automatic Restart on Failures
Scalable In-memory Checkpoint with Automatic Restart on Failures Xiang Ni, Esteban Meneses, Laxmikant V. Kalé Parallel Programming Laboratory University of Illinois at Urbana-Champaign November, 2012 8th
More informationMaximizing Memory Performance for ANSYS Simulations
Maximizing Memory Performance for ANSYS Simulations By Alex Pickard, 2018-11-19 Memory or RAM is an important aspect of configuring computers for high performance computing (HPC) simulation work. The performance
More informationManaging Hardware Power Saving Modes for High Performance Computing
Managing Hardware Power Saving Modes for High Performance Computing Second International Green Computing Conference 2011, Orlando Timo Minartz, Michael Knobloch, Thomas Ludwig, Bernd Mohr timo.minartz@informatik.uni-hamburg.de
More informationarxiv: v1 [cs.dc] 7 Oct 2017
Pattern-based Modeling of High-Performance Computing Resilience Saurabh Hukerikar, Christian Engelmann arxiv:1710.02627v1 [cs.dc] 7 Oct 2017 Computer Science and Mathematics Division Oak Ridge National
More informationSGI Overview. HPC User Forum Dearborn, Michigan September 17 th, 2012
SGI Overview HPC User Forum Dearborn, Michigan September 17 th, 2012 SGI Market Strategy HPC Commercial Scientific Modeling & Simulation Big Data Hadoop In-memory Analytics Archive Cloud Public Private
More informationAdvanced Data Placement via Ad-hoc File Systems at Extreme Scales (ADA-FS)
Advanced Data Placement via Ad-hoc File Systems at Extreme Scales (ADA-FS) Understanding I/O Performance Behavior (UIOP) 2017 Sebastian Oeste, Mehmet Soysal, Marc-André Vef, Michael Kluge, Wolfgang E.
More informationLeveraging Software-Defined Storage to Meet Today and Tomorrow s Infrastructure Demands
Leveraging Software-Defined Storage to Meet Today and Tomorrow s Infrastructure Demands Unleash Your Data Center s Hidden Power September 16, 2014 Molly Rector CMO, EVP Product Management & WW Marketing
More informationEfficiency Evaluation of the Input/Output System on Computer Clusters
Efficiency Evaluation of the Input/Output System on Computer Clusters Sandra Méndez, Dolores Rexachs and Emilio Luque Computer Architecture and Operating System Department (CAOS) Universitat Autònoma de
More informationFine-grained Metadata Journaling on NVM
32nd International Conference on Massive Storage Systems and Technology (MSST 2016) May 2-6, 2016 Fine-grained Metadata Journaling on NVM Cheng Chen, Jun Yang, Qingsong Wei, Chundong Wang, and Mingdi Xue
More informationGot Burst Buffer. Now What? Early experiences, exciting future possibilities, and what we need from the system to make it work
Got Burst Buffer. Now What? Early experiences, exciting future possibilities, and what we need from the system to make it work The Salishan Conference on High-Speed Computing April 26, 2016 Adam Moody
More informationFlashTier: A Lightweight, Consistent and Durable Storage Cache
FlashTier: A Lightweight, Consistent and Durable Storage Cache Mohit Saxena PhD Candidate University of Wisconsin-Madison msaxena@cs.wisc.edu Flash Memory Summit 2012 Santa Clara, CA Flash is a Good Cache
More informationTracing and Visualization of Energy Related Metrics
Tracing and Visualization of Energy Related Metrics 8th Workshop on High-Performance, Power-Aware Computing 2012, Shanghai Timo Minartz, Julian Kunkel, Thomas Ludwig timo.minartz@informatik.uni-hamburg.de
More informationReducing Network Contention with Mixed Workloads on Modern Multicore Clusters
Reducing Network Contention with Mixed Workloads on Modern Multicore Clusters Matthew Koop 1 Miao Luo D. K. Panda matthew.koop@nasa.gov {luom, panda}@cse.ohio-state.edu 1 NASA Center for Computational
More informationReDefine Enterprise Storage
ReDefine Enterprise Storage What s New With VMAX 1 INDUSTRY S FIRST ENTERPRISE DATA PLATFORM 2 LOW LATENCY Flash optimized NO DOWNTIME Always On availability BUSINESS ORIENTED 1-Click Service Levels CLOUD
More informationENERGY-EFFICIENT VISUALIZATION PIPELINES A CASE STUDY IN CLIMATE SIMULATION
ENERGY-EFFICIENT VISUALIZATION PIPELINES A CASE STUDY IN CLIMATE SIMULATION Vignesh Adhinarayanan Ph.D. (CS) Student Synergy Lab, Virginia Tech INTRODUCTION Supercomputers are constrained by power Power
More informationUtilitarian Performance Isolation in Shared SSDs
Utilitarian Performance Isolation in Shared SSDs Bryan S. Kim (Seoul National University, Korea) Flash storage landscape Exploit parallelism! Expose parallelism! Host system NVMe MQ blk IO (SYSTOR13) NVMeDirect
More informationBenchmark: In-Memory Database System (IMDS) Deployed on NVDIMM
Benchmark: In-Memory Database System (IMDS) Deployed on NVDIMM Presented by Steve Graves, McObject and Jeff Chang, AgigA Tech Santa Clara, CA 1 The Problem: Memory Latency NON-VOLATILE MEMORY HIERARCHY
More informationRadiation-Induced Error Criticality In Modern HPC Parallel Accelerators
Radiation-Induced Error Criticality In Modern HPC Parallel Accelerators Presented by: Christopher Boggs, Clayton Connors on 09/26/2018 Authored by: Daniel Oliveira, Laercio Pilla, Mauricio Hanzich, Vinicius
More informationINTEGRATING HPFS IN A CLOUD COMPUTING ENVIRONMENT
INTEGRATING HPFS IN A CLOUD COMPUTING ENVIRONMENT Abhisek Pan 2, J.P. Walters 1, Vijay S. Pai 1,2, David Kang 1, Stephen P. Crago 1 1 University of Southern California/Information Sciences Institute 2
More informationSoft Updates Made Simple and Fast on Non-volatile Memory
Soft Updates Made Simple and Fast on Non-volatile Memory Mingkai Dong, Haibo Chen Institute of Parallel and Distributed Systems, Shanghai Jiao Tong University @ NVMW 18 Non-volatile Memory (NVM) ü Non-volatile
More informationApplication-Transparent Checkpoint/Restart for MPI Programs over InfiniBand
Application-Transparent Checkpoint/Restart for MPI Programs over InfiniBand Qi Gao, Weikuan Yu, Wei Huang, Dhabaleswar K. Panda Network-Based Computing Laboratory Department of Computer Science & Engineering
More informationStructuring PLFS for Extensibility
Structuring PLFS for Extensibility Chuck Cranor, Milo Polte, Garth Gibson PARALLEL DATA LABORATORY Carnegie Mellon University What is PLFS? Parallel Log Structured File System Interposed filesystem b/w
More informationStore Process Analyze Collaborate Archive Cloud The HPC Storage Leader Invent Discover Compete
Store Process Analyze Collaborate Archive Cloud The HPC Storage Leader Invent Discover Compete 1 DDN Who We Are 2 We Design, Deploy and Optimize Storage Systems Which Solve HPC, Big Data and Cloud Business
More informationIoan Raicu Distributed Systems Laboratory Computer Science Department University of Chicago
Running 1 Million Jobs in 10 Minutes via the Falkon Fast and Light-weight Ioan Raicu Distributed Systems Laboratory Computer Science Department University of Chicago In Collaboration with: Ian Foster,
More informationThe Dangers and Complexities of SQLite Benchmarking. Dhathri Purohith, Jayashree Mohan and Vijay Chidambaram
The Dangers and Complexities of SQLite Benchmarking Dhathri Purohith, Jayashree Mohan and Vijay Chidambaram 2 3 Benchmarking SQLite is Non-trivial! Benchmarking complex systems in a repeatable fashion
More informationSoftware-Defined Data Infrastructure Essentials
Software-Defined Data Infrastructure Essentials Cloud, Converged, and Virtual Fundamental Server Storage I/O Tradecraft Greg Schulz Server StorageIO @StorageIO 1 of 13 Contents Preface Who Should Read
More informationSchema-Agnostic Indexing with Azure Document DB
Schema-Agnostic Indexing with Azure Document DB Introduction Azure DocumentDB is Microsoft s multi-tenant distributed database service for managing JSON documents at Internet scale Multi-tenancy is an
More informationarxiv: v2 [cs.dc] 2 May 2017
High Performance Data Persistence in Non-Volatile Memory for Resilient High Performance Computing Yingchao Huang University of California, Merced yhuang46@ucmerced.edu Kai Wu University of California,
More informationTools for Social Networking Infrastructures
Tools for Social Networking Infrastructures 1 Cassandra - a decentralised structured storage system Problem : Facebook Inbox Search hundreds of millions of users distributed infrastructure inbox changes
More informationNEXTGenIO Performance Tools for In-Memory I/O
NEXTGenIO Performance Tools for In- I/O holger.brunst@tu-dresden.de ZIH, Technische Universität Dresden 22 nd -23 rd March 2017 Credits Intro slides by Adrian Jackson (EPCC) A new hierarchy New non-volatile
More informationExpand In-Memory Capacity at a Fraction of the Cost of DRAM: AMD EPYCTM and Ultrastar
White Paper March, 2019 Expand In-Memory Capacity at a Fraction of the Cost of DRAM: AMD EPYCTM and Ultrastar Massive Memory for AMD EPYC-based Servers at a Fraction of the Cost of DRAM The ever-expanding
More informationIntroduction to HPC Parallel I/O
Introduction to HPC Parallel I/O Feiyi Wang (Ph.D.) and Sarp Oral (Ph.D.) Technology Integration Group Oak Ridge Leadership Computing ORNL is managed by UT-Battelle for the US Department of Energy Outline
More informationOn the Use of Burst Buffers for Accelerating Data-Intensive Scientific Workflows
On the Use of Burst Buffers for Accelerating Data-Intensive Scientific Workflows Rafael Ferreira da Silva, Scott Callaghan, Ewa Deelman 12 th Workflows in Support of Large-Scale Science (WORKS) SuperComputing
More informationDesign and Architecture of Dell Acceleration Appliances for Database (DAAD): A Practical Approach with High Availability Guaranteed
Design and Architecture of Dell Acceleration Appliances for Database (DAAD): A Practical Approach with High Availability Guaranteed Kai Yu, Yuxiang Gao Dell Global Solutions Engineering Group Peng Zhang,
More informationLoad Balancing for Parallel Multi-core Machines with Non-Uniform Communication Costs
Load Balancing for Parallel Multi-core Machines with Non-Uniform Communication Costs Laércio Lima Pilla llpilla@inf.ufrgs.br LIG Laboratory INRIA Grenoble University Grenoble, France Institute of Informatics
More information* Contributed while interning at SAP. September 1 st, 2017 PUBLIC
Adaptive Recovery for SCM-Enabled Databases Ismail Oukid (TU Dresden & SAP), Daniel Bossle* (SAP), Anisoara Nica (SAP), Peter Bumbulis (SAP), Wolfgang Lehner (TU Dresden), Thomas Willhalm (Intel) * Contributed
More informationLustre* is designed to achieve the maximum performance and scalability for POSIX applications that need outstanding streamed I/O.
Reference Architecture Designing High-Performance Storage Tiers Designing High-Performance Storage Tiers Intel Enterprise Edition for Lustre* software and Intel Non-Volatile Memory Express (NVMe) Storage
More informationEnhancing Checkpoint Performance with Staging IO & SSD
Enhancing Checkpoint Performance with Staging IO & SSD Xiangyong Ouyang Sonya Marcarelli Dhabaleswar K. Panda Department of Computer Science & Engineering The Ohio State University Outline Motivation and
More informationNetwork bandwidth is a performance bottleneck for cluster computing. Especially for clusters built with SMP machines.
Mingzhe Li Motivation Network bandwidth is a performance bottleneck for cluster computing. Especially for clusters built with SMP machines. Multirail network is an efficient way to alleviate this problem
More informationMiAMI: Multi-Core Aware Processor Affinity for TCP/IP over Multiple Network Interfaces
MiAMI: Multi-Core Aware Processor Affinity for TCP/IP over Multiple Network Interfaces Hye-Churn Jang Hyun-Wook (Jin) Jin Department of Computer Science and Engineering Konkuk University Seoul, Korea {comfact,
More informationHYCOM Performance Benchmark and Profiling
HYCOM Performance Benchmark and Profiling Jan 2011 Acknowledgment: - The DoD High Performance Computing Modernization Program Note The following research was performed under the HPC Advisory Council activities
More informationImproving Application Performance and Predictability using Multiple Virtual Lanes in Modern Multi-Core InfiniBand Clusters
Improving Application Performance and Predictability using Multiple Virtual Lanes in Modern Multi-Core InfiniBand Clusters Hari Subramoni, Ping Lai, Sayantan Sur and Dhabhaleswar. K. Panda Department of
More informationPaperspace. Architecture Overview. 20 Jay St. Suite 312 Brooklyn, NY Technical Whitepaper
Architecture Overview Copyright 2016 Paperspace, Co. All Rights Reserved June - 1-2017 Technical Whitepaper Paperspace Whitepaper: Architecture Overview Content 1. Overview 3 2. Virtualization 3 Xen Hypervisor
More informationThe Google File System
The Google File System Sanjay Ghemawat, Howard Gobioff, and Shun-Tak Leung Google* 정학수, 최주영 1 Outline Introduction Design Overview System Interactions Master Operation Fault Tolerance and Diagnosis Conclusions
More informationIME (Infinite Memory Engine) Extreme Application Acceleration & Highly Efficient I/O Provisioning
IME (Infinite Memory Engine) Extreme Application Acceleration & Highly Efficient I/O Provisioning September 22 nd 2015 Tommaso Cecchi 2 What is IME? This breakthrough, software defined storage application
More informationScaling Internet TV Content Delivery ALEX GUTARIN DIRECTOR OF ENGINEERING, NETFLIX
Scaling Internet TV Content Delivery ALEX GUTARIN DIRECTOR OF ENGINEERING, NETFLIX Inventing Internet TV Available in more than 190 countries 104+ million subscribers Lots of Streaming == Lots of Traffic
More informationIntel Xeon Phi архитектура, модели программирования, оптимизация.
Нижний Новгород, 2017 Intel Xeon Phi архитектура, модели программирования, оптимизация. Дмитрий Прохоров, Дмитрий Рябцев, Intel Agenda What and Why Intel Xeon Phi Top 500 insights, roadmap, architecture
More informationArchitecture Exploration of High-Performance PCs with a Solid-State Disk
Architecture Exploration of High-Performance PCs with a Solid-State Disk D. Kim, K. Bang, E.-Y. Chung School of EE, Yonsei University S. Yoon School of EE, Korea University April 21, 2010 1/53 Outline
More informationNewest generation of HP ProLiant DL380 takes #1 position overall on Oracle E-Business Suite Small Model Benchmark
Newest generation of HP ProLiant DL380 takes #1 position overall on Oracle E-Business Suite Small Model Benchmark ProLiant DL380 G6 uses latest Intel Xeon X5570 technology for ultimate performance HP Leadership
More informationPYTHIA: Improving Datacenter Utilization via Precise Contention Prediction for Multiple Co-located Workloads
PYTHIA: Improving Datacenter Utilization via Precise Contention Prediction for Multiple Co-located Workloads Ran Xu (Purdue), Subrata Mitra (Adobe Research), Jason Rahman (Facebook), Peter Bai (Purdue),
More informationThe Google File System
The Google File System Sanjay Ghemawat, Howard Gobioff, and Shun-Tak Leung Google SOSP 03, October 19 22, 2003, New York, USA Hyeon-Gyu Lee, and Yeong-Jae Woo Memory & Storage Architecture Lab. School
More informationExchange 2010 Tested Solutions: 500 Mailboxes in a Single Site Running Hyper-V on Dell Servers
Exchange 2010 Tested Solutions: 500 Mailboxes in a Single Site Running Hyper-V on Dell Servers Rob Simpson, Program Manager, Microsoft Exchange Server; Akshai Parthasarathy, Systems Engineer, Dell; Casey
More information