SAN DIEGO SUPERCOMPUTER CENTER at the UNIVERSITY OF CALIFORNIA, SAN DIEGO Gordon: NSF Flash-based System for Data-intensive Science Mahidhar Tatineni 37 th HPC User Forum Seattle, WA Sept. 14, 2010 PIs: Michael L. Norman, Allan Snavely San Diego Supercomputer Center

SAN DIEGO SUPERCOMPUTER CENTER at the UNIVERSITY OF CALIFORNIA, SAN DIEGO What is Gordon? A “data-intensive” supercomputer based on SSD flash memory and virtual shared memory SW Emphasizes MEM and IOPS over FLOPS A system designed to accelerate access to massive data bases being generated in all fields of science, engineering, medicine, and social science The NSF’s most recent Track 2 award to the San Diego Supercomputer Center (SDSC) Coming Summer 2011

SAN DIEGO SUPERCOMPUTER CENTER at the UNIVERSITY OF CALIFORNIA, SAN DIEGO Michael L. Norman Principal Investigator Director, SDSC Allan Snavely Co-Principal Investigator Project Scientist

SAN DIEGO SUPERCOMPUTER CENTER at the UNIVERSITY OF CALIFORNIA, SAN DIEGO Why Gordon? Growth of digital data is exponential “data tsunami” Driven by advances in digital detectors, networking, and storage technologies Making sense of it all is the new imperative data analysis workflows data mining visual analytics multiple-database queries data-driven applications

SAN DIEGO SUPERCOMPUTER CENTER at the UNIVERSITY OF CALIFORNIA, SAN DIEGO Accelerating universe SurveyArea (sq. deg.) Start dateImage Data (PB) Object Catalog (PB) Pan-STARRS-130, Dark Energy Survey 5, Pan-STARRS-430, Large Synoptic Survey Telescope 20,000~ Joint Dark Energy Mission 28,000~2015~60~30 Cosmological Dark Energy Surveys

SAN DIEGO SUPERCOMPUTER CENTER at the UNIVERSITY OF CALIFORNIA, SAN DIEGO Gordon is designed specifically for data- intensive HPC applications Such applications involve “very large data-sets or very large input-output requirements” (NSF Track 2D RFP) Two data-intensive application classes are important and growing Data Mining “the process of extracting hidden patterns from data… with the amount of data doubling every three years, data mining is becoming an increasingly important tool to transform this data into information.” Wikipedia Data-Intensive Predictive Science solution of scientific problems via simulations that generate large amounts of data

SAN DIEGO SUPERCOMPUTER CENTER at the UNIVERSITY OF CALIFORNIA, SAN DIEGO Red Shift: Data keeps moving further away from the CPU with every turn of Moore’s Law data due to Dean Klein of Micron Disk Access Time

SAN DIEGO SUPERCOMPUTER CENTER at the UNIVERSITY OF CALIFORNIA, SAN DIEGO The Memory Hierarchy of a Typical HPC Cluster Shared memory programming Message passing programming Latency Gap Disk I/O

SAN DIEGO SUPERCOMPUTER CENTER at the UNIVERSITY OF CALIFORNIA, SAN DIEGO The Memory Hierarchy of Gordon Shared memory programming Disk I/O

SAN DIEGO SUPERCOMPUTER CENTER at the UNIVERSITY OF CALIFORNIA, SAN DIEGO Gordon Architecture: “Supernode” 32 Appro Extreme-X compute nodes Dual processor Intel Sandy Bridge 240 GFLOPS 64 GB 2 Appro Extreme-X IO nodes Intel SSD drives 4 TB ea. 560,000 IOPS ScaleMP vSMP virtual shared memory 2 TB RAM aggregate 8 TB SSD aggregate 240 GF Comp. Node 64 GB RAM 240 GF Comp. Node 64 GB RAM 4 TB SSD I/O Node vSMP memory virtualization

SAN DIEGO SUPERCOMPUTER CENTER at the UNIVERSITY OF CALIFORNIA, SAN DIEGO Gordon Architecture: Full Machine 32 supernodes = 1024 compute nodes Dual rail QDR Infiniband network 3D torus (4x4x4) 4 PB rotating disk parallel file system >100 GB/s SN DDDDDD

SAN DIEGO SUPERCOMPUTER CENTER at the UNIVERSITY OF CALIFORNIA, SAN DIEGO Gordon Aggregate Capabilities Speed245 TFLOPS Mem (RAM)64 TB Mem (SSD)256 TB Mem (RAM+SSD)320 TB Ratio (MEM/SPEED)1.31 BYTES/FLOP IO rate to SSDs35 Million IOPS Network bandwidth16 GB/s bi-directional Network latency 1  sec. Disk storage4 PB Disk IO Bandwidth>100 GB/sec

SAN DIEGO SUPERCOMPUTER CENTER at the UNIVERSITY OF CALIFORNIA, SAN DIEGO Dash*: a working prototype of Gordon *available as a TeraGrid resource

SAN DIEGO SUPERCOMPUTER CENTER at the UNIVERSITY OF CALIFORNIA, SAN DIEGO DASH Architecture 2 Nehalem quad- core CPUs 48GB DDR3 memory Compute node … 16 Compute node I/O node InfiniBand CPU & memory RAID controllers/HBAs (Host Bus Adapters) Intel® X25-E 64GB flash drive … 16 I/O node

SAN DIEGO SUPERCOMPUTER CENTER at the UNIVERSITY OF CALIFORNIA, SAN DIEGO DASH Architecture 15 Compute node … 16 Compute node I/O node InfiniBand Just a cluster ???

SAN DIEGO SUPERCOMPUTER CENTER at the UNIVERSITY OF CALIFORNIA, SAN DIEGO Supernode 128 cores 768GB DRAM 1TB flash drives Supernode 128 cores 768GB DRAM 1TB flash drives Supernode 128 cores 768GB DRAM 1TB flash drives DASH Architecture 16 vSMP system Compute node … 16 Compute node I/O node InfiniBand Supernode 128 cores 768GB DRAM 1TB flash drives

SAN DIEGO SUPERCOMPUTER CENTER at the UNIVERSITY OF CALIFORNIA, SAN DIEGO CPU & memory I/O nodeSoftware RAID 0 I/O Node: Original Configuration 17 RAID controller 64GB flash 64GB flash 64GB flash … 8 Hardware RAID 0 RAID controller 64GB flash 64GB flash 64GB flash … 8 Hardware RAID 0 Achieved only 15% of the upper bound after exhaustive tuning. The embedded processor is the bottleneck.

SAN DIEGO SUPERCOMPUTER CENTER at the UNIVERSITY OF CALIFORNIA, SAN DIEGO I/O Node: New Configuration 18 CPU & memory I/O node Software RAID 0 HBA 64GB flash 64GB flash 64GB flash … 4 HBA 64GB flash 64GB flash 64GB flash … 4 HBA 64GB flash 64GB flash 64GB flash … 4 HBA 64GB flash 64GB flash 64GB flash … 4 Achieved up to 80% of the upper bound. Peripheral hardware designed for spinning disks cannot satisfy flash drives!

SAN DIEGO SUPERCOMPUTER CENTER at the UNIVERSITY OF CALIFORNIA, SAN DIEGO I/O System Configuration CPU: 2 Intel® Nehalem quad-core 2.4GHz Memory: 48GB DDR3 Flash drives: 16 Intel® X25-E 64GB SLC SATA Benchmark: IOR and XDD File system: XFS 19

SAN DIEGO SUPERCOMPUTER CENTER at the UNIVERSITY OF CALIFORNIA, SAN DIEGO DASH I/O Node Testing* Distributed shared memory + flash drives Prototype system: DASH Design space exploration with 16,800 tests Stripe sizes Stripe widths File systems I/O schedulers Queue depths Revealed hardware and software issues RAID controller processor MSI per-vector masking File system cannot handle high IOPS I/O schedulers designed for spinning disks Tuning during testing improved performance by about 9x. * Detailed info in TeraGrid 2010 paper: “DASH-IO: an Empirical Study of Flash-based IO for HPC” Jiahua He, Jeffrey Bennett, and Allan Snavely 20

SAN DIEGO SUPERCOMPUTER CENTER at the UNIVERSITY OF CALIFORNIA, SAN DIEGO The I/O Tuning Story 21

SAN DIEGO SUPERCOMPUTER CENTER at the UNIVERSITY OF CALIFORNIA, SAN DIEGO DASH vSMP Node Tests STREAM memory benchmark GAMESS standard benchmark problem Early user examples Genomic sequence assembly code (Velvet). Successfully run on Dash with 178GB of memory used. CMMAP cloud data analysis with data transposition in memory. Early tests run with ~130GB of data.

SAN DIEGO SUPERCOMPUTER CENTER at the UNIVERSITY OF CALIFORNIA, SAN DIEGO DASH – Applications using flash as scratch space Several HPC applications have a substantial per core (local) I/O component (primarily scratch files). Examples are Abaqus, NASTRAN, QChem. Standard Abaqus test cases (S2A1, S4B) were run on Dash to compare performance between local hard disk and SSDs. *Lustre is not optimal for such I/O. S4B test took 18920s. HDD SSD S2A1, 8cores, 1node test4058.2s2964.9s S4B, 8cores, 1 node test*12198s9604.8s

SAN DIEGO SUPERCOMPUTER CENTER at the UNIVERSITY OF CALIFORNIA, SAN DIEGO Dash wins SC09 Storage Challenge at SC09

SAN DIEGO SUPERCOMPUTER CENTER at the UNIVERSITY OF CALIFORNIA, SAN DIEGO 3 Application Benchmarks Massive graph traversal Semantic web search Astronomical database queries Identification of transient objects Biological networks database queries Protein interactions

SAN DIEGO SUPERCOMPUTER CENTER at the UNIVERSITY OF CALIFORNIA, SAN DIEGO Graph Networks Search (BFS) Breadth-first-search on 200GB graph network

SAN DIEGO SUPERCOMPUTER CENTER at the UNIVERSITY OF CALIFORNIA, SAN DIEGO NIH Biological Networks Pathway Analysis Interaction networks or graphs occur in many disciplines, e.g. epidemiology, phylogenetics and systems biology Performance is limited by latency of a Database query and aggregate amount of fast storage available

SAN DIEGO SUPERCOMPUTER CENTER at the UNIVERSITY OF CALIFORNIA, SAN DIEGO Biological Networks Query timing

SAN DIEGO SUPERCOMPUTER CENTER at the UNIVERSITY OF CALIFORNIA, SAN DIEGO Palomar Transient Factory (PTF) Nightly wide-field surveys using Palomar Schmidt telescope Image data sent to LBL for archive/analysis 100 new transients every minute Large, random queries across multiple databases for IDs

SAN DIEGO SUPERCOMPUTER CENTER at the UNIVERSITY OF CALIFORNIA, SAN DIEGO PTF-DB Transient Search Random Queries requesting very small chunks of data about the candidate observations

SAN DIEGO SUPERCOMPUTER CENTER at the UNIVERSITY OF CALIFORNIA, SAN DIEGO Trestles – Coming Soon! Trestles will work with and span the deployments of SDSC’s recently introduced Dash system and the larger Gordon data-intensive system. To be configured by SDSC and Appro, Trestles is based on quad-socket, 8-core AMD Magny-Cours compute nodes connected via a QDR InfiniBand fabric. Trestles will have 324 nodes, 10,368 processor cores, a peak speed of 100 teraflop/s, and 38 terabytes of flash memory. Each of the 324 nodes will have 32 cores, 64 GB of DDR3 memory, and 120 GB of flash memory.

SAN DIEGO SUPERCOMPUTER CENTER at the UNIVERSITY OF CALIFORNIA, SAN DIEGO Conclusions Gordon architecture customized for data-intensive applications, but built entirely from commodity parts Basically a Linux cluster with Large RAM memory/core Large amount of flash SSD Virtual shared memory software  10 TB of storage accessible from a single core  shared memory parallelism for higher performance Dash prototype accelerates real applications by 2-100x relative to disk depending on memory access patterns Random I/O accelerated the most

SAN DIEGO SUPERCOMPUTER CENTER at the UNIVERSITY OF CALIFORNIA, SAN DIEGO Dash – STREAM on vSMP (test results)