A protocol reconfiguration and optimization system for MPI

Modern high performance computing (HPC) applications, for example adaptive mesh refinement and multi-physics codes, have dynamic communication characteristics which result in poor performance on current Message Passing Interface (MPI) implementations. The degraded application performance can be attributed to a mismatch between changing application requirements and static communication library functionality. To improve the performance of these applications, MPI libraries should change their protocol functionality in response to changing application requirements, and tailor their functionality to take advantage of hardware capabilities. This dissertation describes Protocol Reconfiguration and Optimization system for MPI (PRO-MPI), a framework for constructing profile-driven reconfigurable MPI libraries; these libraries use past application characteristics (profiles) to dynamically change their functionality to match the changing application requirements. The framework addresses the challenges of designing and implementing the reconfigurable MPI libraries, which include collecting and reasoning about application characteristics to drive the protocol reconfiguration and defining abstractions required for implementing these reconfigurations. Two prototype reconfigurable MPI implementations based on the framework - Open PRO-MPI and Cactus PRO-MPI - are also presented to demonstrate the utility of the framework. To demonstrate the effectiveness of reconfigurable MPI libraries, this dissertation presents experimental results to show the impact of using these libraries on the application performance. The results show that PRO-MPI improves the performance of important HPC applications and benchmarks. They also show that HyperCLaw performance improves by approximately 22% when exact profiles are available, and HyperCLaw performance improves by approximately 18% when only approximate profiles are available

Effects of Communication Protocol Stack Offload on Parallel Performance in Clusters

The primary research objective of this dissertation is to demonstrate that the effects of communication protocol stack offload (CPSO) on application execution time can be attributed to the following two complementary sources. First, the application-specific computation may be executed concurrently with the asynchronous communication performed by the communication protocol stack offload engine. Second, the protocol stack processing can be accelerated or decelerated by the offload engine. These two types of performance effects can be quantified with the use of the degree of overlapping Do and degree of acceleration Daccs. The composite communication speedup metrics S_comm(Do, Daccs) can be used in order to quantify the combined effects of the protocol stack offload. This dissertation thesis is validated empirically. The degree of overlapping Do, the degree of acceleration Daccs, and the communication speedup Scomm characteristic of the system configurations under test are derived in the course of experiments performed for the system configurations of interest. It is shown that the proposed metrics adequately describe the effects of the protocol stack offload on the application execution time. Additionally, a set of analytical models of the networking subsystem of a PC-based cluster node is developed. As a result of the modeling, the metrics Do, Daccs, and Scomm are obtained. The models are evaluated as to their complexity and precision by comparing the modeling results with the measured values of Do, Daccs, and Scomm. The primary contributions of this dissertation research are as follows. First, the metric Daccs and Scomm are introduced in order to complement the Do metric in its use for evaluation of the effects of optimizations in the networking subsystem on parallel performance in clusters. The metrics are shown to adequately describe CPSO performance effects. Second, a method for assessing performance effects of CPSO scenarios on application performance is developed and presented. Third, a set of analytical models of cluster node networking subsystems with CPSO capability is developed and characterised as to their complexity and precision of the prediction of the Do and Daccs metrics

Evaluation of the network performance in a high performance computing cloud

Pilvipalvelut mahdollistavat resurssien joustavan käytön. Erityisesti niin sanoituissa Infrastructure-as-a-Service -pilvipalveluissa käyttäjän voivat virtualisoinnin kautta ajaa sovelluksiaan omissa virtuaalikoneissaan ja siten muokata sovellusten ajoympäristöä omien tarpeidensa mukaan. Näissä palveluissa käytettävä virtualisointi lisää yleisrasitetta, joka heikentää sekä laskennan että I/O-laitteiden suorituskykyä. Tässä työssä evaluoidaan tällaisen pilvipalvelun verkon suorituskykyä. Palvelussa käytetty verkkoteknologia pohjautuu InfiniBand-arkkitehtuuriin, joka on yleinen teknologia erityisesti suurteholaskennassa käytettävissä klusterijärjestelmissä. Evaluointimenetelmät tutkivat verkon latenssia ja läpisyöttöä (engl. throughput) eri skenaarioissa, joissa suureita tutkitaan sekä ilman virtualisointia että virtualisoinnin kanssa. Skenaarioiden tarkoituksena on kartoittaa yleisrasitteeseen voimakkaimmin vaikuttavia tekijöitä. Tämän lisäksi työssä evaluoidaan erityistä SR-IOV-teknologiaa, joka mahdollistaa fyysisen laitteen esittämisen joukkona virtuaalikoneisiin liitettäviä virtuaalilaitteita. Teknologian avulla voidaan yleisesti tehostaa I/O laitteiden suorituskykyä virtuaalikoneissa. Tämän evaluoinnin yhteydessä käytettävissä InfiniBand-laitteissa on SR-IOV-tuesta ollut kehitysversio, jota on testettu evaluoitavassa järjestelmässä. Evaluoinnin tulokset osoittavat käytettävän tunnelointiprotokollan sekä virtualisoinnin I/O-tuen puutteen aiheuttavan suurimmat suorituskyvyn menetykset evaluoiduissa skenaarioissa. Evaluoitu SR-IOV-teknologia on tulosten perusteella kaikissa tapauksissa suositeltava käyttöönotettava teknologia suorituskyvyn parantamiseksi.The cloud services enable a flexible use of resources. Especially in so called Infrasturcture-as-a-Service style cloud services the users can run their own applications in their own virtual machines and so customize the whole execution environment as needed. However the virtualization introduces an overhead which decreases the performance of computation and I/O-device access. This work contains a network performance evaluation of this kind of cloud service. The service uses InfiniBand as its network interconnect solution, a technology often used in high performance computing clusters. The evaluation methods study the network latency and throughput in different scenarios. In these scenarios the metrics are studied with and without virtualization. The purpose of these scenarios is to study the major contributing sources for the introduced overhead. This work also contains an evaluation of SR-IOV technology, which enables the mapping from physical device into multiple virtual functions which can be assigned directly to virtual machines. The technology can be used to improve the performance of I/O devices. In this work the SR-IOV technology is studied with InfiniBand devices which are currently having an experimental support for SR-IOV. The evaluation results show that the tunneling protocol used and the lack of hardware support for virtualized I/O are causing the biggest performance losses in the evaluated scenarios. The evaluated SR-IOV technology is, based on the evaluated scenarios, desired in all cases to improve the performance

Virtual InfiniBand Clusters for HPC Clouds

High Performance Computing (HPC) employs fast interconnect technologies to provide low communication and synchronization latencies for tightly coupled parallel compute jobs. Contemporary HPC clusters have a xed capacity and static runtime environments; they cannot elastically adapt to dynamic workloads, and provide a limited selection of applications, libraries, and system software. In contrast, a cloud model for HPC clusters promises more exibility, as it provides elastic virtual clusters to be available on-demand. This is not possible with physically owned clusters. In this paper, we present an approach that makes it possible to use InfiniBand clusters for HPC cloud computing. We propose a performance-driven design of an HPC IaaS layer for In niBand, which provides throughput and latency-aware virtualization of nodes, networks, and network topologies, as well as an approach to an HPC-aware, multi-tenant cloud management system for elastic virtualized HPC compute clusters

A complete and efficient CUDA-sharing solution for HPC clusters

In this paper we detail the key features, architectural design, and implementation of rCUDA, an advanced framework to enable remote and transparent GPGPU acceleration in HPC clusters. rCUDA allows decoupling GPUs from nodes, forming pools of shared accelerators, which brings enhanced flexibility to cluster configurations. This opens the door to configurations with fewer accelerators than nodes, as well as permits a single node to exploit the whole set of GPUs installed in the cluster. In our proposal, CUDA applications can seamlessly interact with any GPU in the cluster, independently of its physical location. Thus, GPUs can be either distributed among compute nodes or concentrated in dedicated GPGPU servers, depending on the cluster administrator’s policy. This proposal leads to savings not only in space but also in energy, acquisition, and maintenance costs. The performance evaluation in this paper with a series of benchmarks and a production application clearly demonstrates the viability of this proposal. Concretely, experiments with the matrix–matrix product reveal excellent performance compared with regular executions on the local GPU; on a much more complex application, the GPU-accelerated LAMMPS, we attain up to 11x speedup employing 8 remote accelerators from a single node with respect to a 12-core CPU-only execution. GPGPU service interaction in compute nodes, remote acceleration in dedicated GPGPU servers, and data transfer performance of similar GPU virtualization frameworks are also evaluated. 2014 Elsevier B.V. All rights reserved.This work was supported by the Spanish Ministerio de Economia y Competitividad (MINECO) and by FEDER funds under Grant TIN2012-38341-004-01. It was also supported by MINECO, FEDER funds, under Grant TIN2011-23283, and by the Fundacion Caixa-Castello Bancaixa, Grant P11B2013-21. This work was also supported in part by the U.S. Department of Energy, Office of Science, under contract DE-AC02-06CH11357. Authors are grateful for the generous support provided by Mellanox Technologies to the rCUDA Project. The authors would also like to thank Adrian Castello, member of The rCUDA Development Team, for his hard work on rCUDA.Peña Monferrer, AJ.; Reaño González, C.; Silla Jiménez, F.; Mayo Gual, R.; Quintana-Orti, ES.; Duato Marín, JF. (2014). A complete and efficient CUDA-sharing solution for HPC clusters. Parallel Computing. 40(10):574-588. https://doi.org/10.1016/j.parco.2014.09.011S574588401

Design and Evaluation of Low-Latency Communication Middleware on High Performance Computing Systems

[Resumen]El interés en Java para computación paralela está motivado por sus interesantes características, tales como su soporte multithread, portabilidad, facilidad de aprendizaje,alta productividad y el aumento significativo en su rendimiento omputacional. No obstante, las aplicaciones paralelas en Java carecen generalmente de mecanismos de comunicación eficientes, los cuales utilizan a menudo protocolos basados en sockets incapaces de obtener el máximo provecho de las redes de baja latencia, obstaculizando la adopción de Java en computación de altas prestaciones (High Per- formance Computing, HPC). Esta Tesis Doctoral presenta el diseño, implementación y evaluación de soluciones de comunicación en Java que superan esta limitación. En consecuencia, se desarrollaron múltiples dispositivos de comunicación a bajo nivel para paso de mensajes en Java (Message-Passing in Java, MPJ) que aprovechan al máximo el hardware de red subyacente mediante operaciones de acceso directo a memoria remota que proporcionan comunicaciones de baja latencia. También se incluye una biblioteca de paso de mensajes en Java totalmente funcional, FastMPJ, en la cual se integraron los dispositivos de comunicación. La evaluación experimental ha mostrado que las primitivas de comunicación de FastMPJ son competitivas en comparación con bibliotecas nativas, aumentando significativamente la escalabilidad de aplicaciones MPJ. Por otro lado, esta Tesis analiza el potencial de la computación en la nube (cloud computing) para HPC, donde el modelo de distribución de infraestructura como servicio (Infrastructure as a Service, IaaS) emerge como una alternativa viable a los sistemas HPC tradicionales. La evaluación del rendimiento de recursos cloud específicos para HPC del proveedor líder, Amazon EC2, ha puesto de manifiesto el impacto significativo que la virtualización impone en la red, impidiendo mover las aplicaciones intensivas en comunicaciones a la nube. La clave reside en un soporte de virtualización apropiado, como el acceso directo al hardware de red, junto con las directrices para la optimización del rendimiento sugeridas en esta Tesis.[Resumo]O interese en Java para computación paralela está motivado polas súas interesantes características, tales como o seu apoio multithread, portabilidade, facilidade de aprendizaxe, alta produtividade e o aumento signi cativo no seu rendemento computacional. No entanto, as aplicacións paralelas en Java carecen xeralmente de mecanismos de comunicación e cientes, os cales adoitan usar protocolos baseados en sockets que son incapaces de obter o máximo proveito das redes de baixa latencia, obstaculizando a adopción de Java na computación de altas prestacións (High Performance Computing, HPC). Esta Tese de Doutoramento presenta o deseño, implementaci ón e avaliación de solucións de comunicación en Java que superan esta limitación. En consecuencia, desenvolvéronse múltiples dispositivos de comunicación a baixo nivel para paso de mensaxes en Java (Message-Passing in Java, MPJ) que aproveitan ao máaximo o hardware de rede subxacente mediante operacións de acceso directo a memoria remota que proporcionan comunicacións de baixa latencia. Tamén se inclúe unha biblioteca de paso de mensaxes en Java totalmente funcional, FastMPJ, na cal foron integrados os dispositivos de comunicación. A avaliación experimental amosou que as primitivas de comunicación de FastMPJ son competitivas en comparación con bibliotecas nativas, aumentando signi cativamente a escalabilidade de aplicacións MPJ. Por outra banda, esta Tese analiza o potencial da computación na nube (cloud computing) para HPC, onde o modelo de distribución de infraestrutura como servizo (Infrastructure as a Service, IaaS) xorde como unha alternativa viable aos sistemas HPC tradicionais. A ampla avaliación do rendemento de recursos cloud específi cos para HPC do proveedor líder, Amazon EC2, puxo de manifesto o impacto signi ficativo que a virtualización impón na rede, impedindo mover as aplicacións intensivas en comunicacións á nube. A clave atópase no soporte de virtualización apropiado, como o acceso directo ao hardware de rede, xunto coas directrices para a optimización do rendemento suxeridas nesta Tese.[Abstract]The use of Java for parallel computing is becoming more promising owing to its appealing features, particularly its multithreading support, portability, easy-tolearn properties, high programming productivity and the noticeable improvement in its computational performance. However, parallel Java applications generally su er from inefficient communication middleware, most of which use socket-based protocols that are unable to take full advantage of high-speed networks, hindering the adoption of Java in the High Performance Computing (HPC) area. This PhD Thesis presents the design, development and evaluation of scalable Java communication solutions that overcome these constraints. Hence, we have implemented several lowlevel message-passing devices that fully exploit the underlying network hardware while taking advantage of Remote Direct Memory Access (RDMA) operations to provide low-latency communications. Moreover, we have developed a productionquality Java message-passing middleware, FastMPJ, in which the devices have been integrated seamlessly, thus allowing the productive development of Message-Passing in Java (MPJ) applications. The performance evaluation has shown that FastMPJ communication primitives are competitive with native message-passing libraries, improving signi cantly the scalability of MPJ applications. Furthermore, this Thesis has analyzed the potential of cloud computing towards spreading the outreach of HPC, where Infrastructure as a Service (IaaS) o erings have emerged as a feasible alternative to traditional HPC systems. Several cloud resources from the leading IaaS provider, Amazon EC2, which speci cally target HPC workloads, have been thoroughly assessed. The experimental results have shown the signi cant impact that virtualized environments still have on network performance, which hampers porting communication-intensive codes to the cloud. The key is the availability of the proper virtualization support, such as the direct access to the network hardware, along with the guidelines for performance optimization suggested in this Thesis

Fast and generic concurrent message-passing

Communication hardware and software have a significant impact on the performance of clusters and supercomputers. Message passing model and the Message-Passing Interface (MPI) is a widely used model of communications in the High-Performance Computing (HPC) community with great success. However, it has recently faced new challenges due to the emergence of many-core architecture and of programming models with dynamic task parallelism, assuming a large number of concurrent, light-weight threads. These applications come from important classes of applications such as graph and data analytics. Using MPI with these languages/runtimes is inefficient because MPI implementation is not able to perform well with threads. Using MPI as a communication middleware is also not efficient since MPI has to provide many abstractions that are not needed for many of the frameworks, thus having extra overheads. In this thesis, we studied MPI performance under the new assumptions. We identified several factors in the message-passing model which were inherently problematic for scalability and performance. Next, we analyzed the communication of a number of graph, threading and data-flow frameworks to identify generic patterns. We then proposed a low-level communication interface (LCI) to bridge the gap between communication architecture and runtime. The core of our idea is to attach to each message a few simple operations which fit better with the current hardware and can be implemented efficiently. We show that with only a few carefully chosen primitives and appropriate design, message-passing under this interface can easily outperform production MPI when running atop of multi-threaded environment. Further, using LCI is simple for various types of usage

Building Distributed Systems with Non-Volatile Main Memories and RDMA Networks

High-performance, byte-addressable non-volatile main memories (NVMMs) allow application developers to combine storage and memory into a single layer. These high-performance storage systems would be especially useful in large-scale data center environments where data is distributed and replicated across multiple servers.Unfortunately, existing approaches of providing remote storage access rest on the assumption that storage is slow, so the cost of the software and protocols is acceptable. Such assumption no longer holds for the fast NVMM. As a result, taking full advantage of NVMMs’ potential will require changes in system software and networking protocol. This thesis focuses on accessing remote NVMM efficiently using remote direct memory access (RDMA) network. RDMA enables a client to directly access memory on a remote machine without involving its local CPU.This thesis first presents Mojim, a system that provides replicated, reliable, and highly-available NVMM as an operating system service. Applications can access data in Mojim using normal load and store instructions while controlling when and how updates propagate to replicas using system calls. Our evaluation shows Mojim adds little overhead to the un-replicated system and provides 0.4x to 2.7x the throughput of the un-replicated system.This thesis then presents Orion, a distributed file system designed from for NVMM and RDMA networks. Traditional distributed file systems are designed for slower hard drives. These slower media incentivizes complex optimizations (e.g., queuing, striping, and batching) around disk accesses. Orion combines file system functions and network operations into a single layer. It provides low latency metadata accesses and outperforms existing distributed file systems by a large margin.Finally, an NVMM application can map files backed by an NVMM file system into its address space, and accesses them using CPU instructions. In this case, RDMA and NVMM file systems introduce duplication of effort on permissions, naming, and address translation. We introduce two changes to the existing RDMA protocol: the file memory region (FileMR) and range based address translation. By eliminating redundant translations, FileMR minimizes the number of translations done at the NIC, reducing the load on the NIC’s translation cache and resulting in application performance improvement by 1.8x - 2.0x

Solutions for the optimization of the software interface on an FPGA-based NIC

The theme of the research is the study of solutions for the optimization of the software interface on FPGA-based Network Interface Cards. The research activity was carried out in the APE group at INFN (Istituto Nazionale di Fisica Nucleare), which has been historically active in designing of high performance scalable networks for hybrid nodes (CPU/GPU) clusters. The result of the research is validated on two projects the APE group is currently working on, both allowing fast prototyping for solutions and hardware-software co-design: APEnet (a PCIe FPGA-based 3D torus network controller) and NaNet (FPGA-based family of NICs mainly dedicated to real-time, low-latency computing systems such as fast control systems or High Energy Physics Data Acquisition Systems). NaNet is also used to validate a GPU-controlled device driver to improve network perfomances, i.e. even lower latency of the communication, while used in combination with existing user-space software. This research is also gaining results in the "Horizon2020 FET-HPC ExaNeSt project", which aims to prototype and develop solutions for some of the crucial problems on the way towards production of Exascale-level Supercomputers, where the APE group is actively contribuiting to the development of the network / interconnection infrastructure