An Efficient Cell List Implementation for Monte Carlo Simulation on GPUs

Maximizing the performance potential of the modern day GPU architecture requires judicious utilization of available parallel resources. Although dramatic reductions can often be obtained through straightforward mappings, further performance improvements often require algorithmic redesigns to more closely exploit the target architecture. In this paper, we focus on efficient molecular simulations for the GPU and propose a novel cell list algorithm that better utilizes its parallel resources. Our goal is an efficient GPU implementation of large-scale Monte Carlo simulations for the grand canonical ensemble. This is a particularly challenging application because there is inherently less computation and parallelism than in similar applications with molecular dynamics. Consistent with the results of prior researchers, our simulation results show traditional cell list implementations for Monte Carlo simulations of molecular systems offer effectively no performance improvement for small systems [5, 14], even when porting to the GPU. However for larger systems, the cell list implementation offers significant gains in performance. Furthermore, our novel cell list approach results in better performance for all problem sizes when compared with other GPU implementations with or without cell lists.Comment: 30 page

Many-core and heterogeneous architectures: programming models and compilation toolchains

1noL'abstract è presente nell'allegato / the abstract is in the attachmentopen677. INGEGNERIA INFORMATInopartially_openembargoed_20211002Barchi, Francesc

Parallel Multiscale Contact Dynamics for Rigid Non-spherical Bodies

The simulation of large numbers of rigid bodies of non-analytical shapes or vastly varying sizes which collide with each other is computationally challenging. The fundamental problem is the identification of all contact points between all particles at every time step. In the Discrete Element Method (DEM), this is particularly difficult for particles of arbitrary geometry that exhibit sharp features (e.g. rock granulates). While most codes avoid non-spherical or non-analytical shapes due to the computational complexity, we introduce an iterative-based contact detection method for triangulated geometries. The new method is an improvement over a naive brute force approach which checks all possible geometric constellations of contact and thus exhibits a lot of execution branching. Our iterative approach has limited branching and high floating point operations per processed byte. It thus is suitable for modern Single Instruction Multiple Data (SIMD) CPU hardware. As only the naive brute force approach is robust and always yields a correct solution, we propose a hybrid solution that combines the best of the two worlds to produce fast and robust contacts. In terms of the DEM workflow, we furthermore propose a multilevel tree-based data structure strategy that holds all particles in the domain on multiple scales in grids. Grids reduce the total computational complexity of the simulation. The data structure is combined with the DEM phases to form a single touch tree-based traversal that identifies both contact points between particle pairs and introduces concurrency to the system during particle comparisons in one multiscale grid sweep. Finally, a reluctant adaptivity variant is introduced which enables us to realise an improved time stepping scheme with larger time steps than standard adaptivity while we still minimise the grid administration overhead. Four different parallelisation strategies that exploit multicore architectures are discussed for the triad of methodological ingredients. Each parallelisation scheme exhibits unique behaviour depending on the grid and particle geometry at hand. The fusion of them into a task-based parallelisation workflow yields promising speedups. Our work shows that new computer architecture can push the boundary of DEM computability but this is only possible if the right data structures and algorithms are chosen

Conflict-Free Networks on Chip for Real Time Systems

[ES] La constante necesidad de un mayor rendimiento para cumplir con la gran demanda de potencia de cómputo de las nuevas aplicaciones, (ej. sistemas de conducción autónoma), obliga a la industria a apostar por la tecnología basada en Sistemas en Chip con Procesadores Multinúcleo (MPSoCs) en sus sistemas embebidos de seguridad-crítica. Los sistemas MPSoCs generalmente incluyen una red en el chip (NoC) para interconectar los núcleos de procesamiento entre ellos, con la memoria y con el resto de recursos compartidos. Desafortunadamente, el uso de las NoCs dificulta alcanzar la predecibilidad en el tiempo, ya que pueden aparecer conflictos en muchos puntos y de forma distribuida a nivel de red. Para afrontar este problema, en esta tesis se propone un nuevo paradigma de diseño para NoCs de tiempo real donde los conflictos en la red son eliminados por diseño. Este nuevo paradigma parte del Grafo de Dependencia de Canales (CDG) para evitar los conflictos de red de forma determinista. Nuestra solución es capaz de inyectar mensajes de forma natural usando un periodo TDM igual al límite teórico óptimo sin la necesidad de usar un proceso offline exigente computacionalmente. La red se ha integrado en un sistema multinúcleo basado en tiles y adaptado a su jerarquía de memoria. Como segunda contribución principal, proponemos un nuevo planificador dinámico y distribuido capaz de alcanzar un rendimiento pico muy cercanos a las NoC basadas en un diseño wormhole sin comprometer sus garantías de tiempo real. El planificador se basa en nuestro diseño de red para explotar sus propiedades clave. Los resultados de nuestra NoC muestran que nuestro diseño garantiza la predecibilidad en el tiempo evitando interferencias en la red entre múltiples aplicaciones ejecutándose concurrentemente. La red siempre garantiza el rendimiento y también mejora el rendimiento respecto al de las redes wormhole en una red 4 x 4 en un factor de 3,7x cuando se inyecta trafico para generar interferencias. En una red 8 x 8 las diferencias son incluso mayores. Además, la red obtiene un ahorro de área total del 10,79% frente a una implementación básica de una red wormhole. El planificador propuesto alcanza una mejora de rendimiento de 6,9x y 14,4x frente la versión básica de la red DCFNoC para redes en forma de malla de 16 y 64 nodos, respectivamente. Cuando lo comparamos frente a un conmutador estándar wormhole se preserva un rendimiento de red del 95% al mismo tiempo que preserva la estricta predecibilidad en el tiempo. Este logro abre la puerta a nuevos diseños de NoCs de alto rendimiento con predecibilidad en el tiempo. Como contribución final, construimos una taxonomía de NoCs basadas en TDM con propiedades de tiempo real. Con esta taxonomía realizamos un análisis exhaustivo para estudiar y comparar desde tiempos de respuesta, a implementaciones con bajo coste, pasando por soluciones de compromiso para diseños de NoCs de tiempo real. Como resultado, obtenemos nuevos diseños de NoCs basadas en TDM.[CA] La constant necessitat d'un major rendiment per a complir amb la gran demanda de potència de còmput de les noves aplicacions, (ex. sistemes de conducció autònoma), obliga la indústria a apostar per la tecnologia basada en Sistemes en Xip amb Processadors Multinucli (MPSoCs) en els seus sistemes embeguts de seguretat-crítica. Els sistemes MPSoCs generalment inclouen una xarxa en el xip (NoC) per a interconnectar els nuclis de processament entre ells, amb la memòria i amb la resta de recursos compartits. Desafortunadament, l'ús de les NoCs dificulta aconseguir la predictibilitat en el temps, ja que poden aparéixer conflictes en molts punts i de forma distribuïda a nivell de xarxa. Per a afrontar aquest problema, en aquesta tesi es proposa un nou paradigma de disseny per a NoCs de temps real on els conflictes en la xarxa són eliminats per disseny. Aquest nou paradigma parteix del Graf de Dependència de Canals (CDG) per a evitar els conflictes de xarxa de manera determinista. La nostra solució és capaç d'injectar missatges de mra natural fent ús d'un període TDM igual al límit teòric òptim sense la necessitat de fer ús d'un procés offline exigent computacionalment. La xarxa s'ha integrat en un sistema multinucli basat en tiles i adaptat a la seua jerarquia de memòria. Com a segona contribució principal, proposem un nou planificador dinàmic i distribuït capaç d'aconseguir un rendiment pic molt pròxims a les NoC basades en un disseny wormhole sense comprometre les seues garanties de temps real. El planificador es basa en el nostre disseny de xarxa per a explotar les seues propietats clau. Els resultats de la nostra NoC mostren que el nostre disseny garanteix la predictibilitat en el temps evitant interferències en la xarxa entre múltiples aplicacions executant-se concurrentment. La xarxa sempre garanteix el rendiment i també millora el rendiment respecte al de les xarxes wormhole en una xarxa 4 x 4 en un factor de 3,7x quan s'injecta trafic per a generar interferències. En una xarxa 8 x 8 les diferències són fins i tot majors. A més, la xarxa obté un estalvi d'àrea total del 10,79% front una implementació bàsica d'una xarxa wormhole. El planificador proposat aconsegueix una millora de rendiment de 6,9x i 14,4x front la versió bàsica de la xarxa DCFNoC per a xarxes en forma de malla de 16 i 64 nodes, respectivament. Quan ho comparem amb un commutador estàndard wormhole es preserva un rendiment de xarxa del 95% al mateix temps que preserva la estricta predictibilitat en el temps. Aquest assoliment obri la porta a nous dissenys de NoCs d'alt rendiment amb predictibilitat en el temps. Com a contribució final, construïm una taxonomia de NoCs basades en TDM amb propietats de temps real. Amb aquesta taxonomia realitzem una anàlisi exhaustiu per a estudiar i comparar des de temps de resposta, a implementacions amb baix cost, passant per solucions de compromís per a dissenys de NoCs de temps real. Com a resultat, obtenim nous dissenys de NoCs basades en TDM.[EN] The ever need for higher performance to cope with the high computational power demands of new applications (e.g autonomous driving systems), forces industry to support technology based on multi-processors system on chip (MPSoCs) in their safety-critical embedded systems. MPSoCs usually include a network-on-chip (NoC) to interconnect the cores between them and, with memory and the rest of shared resources. Unfortunately, the inclusion of NoCs difficults achieving time predictability as network-level conflicts may occur in many points in a distributed manner. To overcome this problem, this thesis proposes a new time-predictable NoC design paradigm where conflicts within the network are eliminated by design. This new paradigm builds on top of the Channel Dependency Graph (CDG) in order to deterministically avoid network conflicts. Our solution is able to naturally inject messages using a TDM period equal to the optimal theoretical bound without the need of using a computationally demanding offline process. The network is integrated in a tile-based manycore system and adapted to its memory hierarchy. As a second main contribution, we propose a novel distributed dynamic scheduler that is able to achieve peak performance close to a wormhole-based NoC design without compromising its real-time guarantees. The scheduler builds on top of our NoC design to exploit its key properties. The results of our NoC show that our design guarantees time predictability avoiding network interference among multiple running applications. The network always guarantees performance and also improves wormhole performance in a 4 x 4 setting by a factor of 3.7x when interference traffic is injected. For a 8 x 8 network differences are even larger. In addition, the network obtains a total area saving of 10.79% over a standard wormhole implementation. The proposed scheduler achieves an overall throughput improvement of 6.9x and 14.4x over a baseline conflict-free NoC for 16 and 64-node meshes, respectively. When compared against a standard wormhole router 95% of its network throughput is preserved while strict timing predictability is kept. This achievement opens the door to new high performance time predictable NoC designs. As a final contribution, we build a taxonomy of TDM-based NoCs with real-time properties. With this taxonomy we perform a comprehensive analysis to study and compare from response time specific, to low resource implementation cost, through trade-off solutions for real-time NoCs designs. As a result, we derive new TDM-based NoC designs.Picornell Sanjuan, T. (2021). Conflict-Free Networks on Chip for Real Time Systems [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/177347TESI

High-Performance and Time-Predictable Embedded Computing

Nowadays, the prevalence of computing systems in our lives is so ubiquitous that we live in a cyber-physical world dominated by computer systems, from pacemakers to cars and airplanes. These systems demand for more computational performance to process large amounts of data from multiple data sources with guaranteed processing times. Actuating outside of the required timing bounds may cause the failure of the system, being vital for systems like planes, cars, business monitoring, e-trading, etc. High-Performance and Time-Predictable Embedded Computing presents recent advances in software architecture and tools to support such complex systems, enabling the design of embedded computing devices which are able to deliver high-performance whilst guaranteeing the application required timing bounds. Technical topics discussed in the book include: Parallel embedded platforms Programming models Mapping and scheduling of parallel computations Timing and schedulability analysis Runtimes and operating systems The work reflected in this book was done in the scope of the European project P SOCRATES, funded under the FP7 framework program of the European Commission. High-performance and time-predictable embedded computing is ideal for personnel in computer/communication/embedded industries as well as academic staff and master/research students in computer science, embedded systems, cyber-physical systems and internet-of-things.info:eu-repo/semantics/publishedVersio

Engineering Research 2014

Table of Contents Health Sensing & Imaging Semiconductors Innovation Peoplehttps://digitalcommons.mtu.edu/engineering-magazine/1010/thumbnail.jp

Master of Science

thesisTo address the need of understanding and optimizing the performance of complex applications and achieving sustained application performance across different architectures, we need performance models and tools that could quantify the theoretical performance and the resultant gap between theoretical and observed performance. This thesis proposes a benchmark-driven Roofline Model Toolkit to provide theoretical and achievable performance, and their resultant gap for multicore, manycore, and accelerated architectures. Roofline micro benchmarks are specialized to quantify the behavior of different architectural features. Compared to previous work on performance characterization, these micro benchmarks focus on capturing the performance of each level of the memory hierarchy, along with thread-level parallelism(TLP), instruction-level parallelism(ILP), and explicit Single Instruction, Multiple Data(SIMD) parallelism, measured in the context of the compilers and runtime environment on the target architecture. We also developed benchmarks to explore detailed memory subsystems behaviors and evaluate parallelization overhead. Beyond on-chip performance, we measure sustained Peripheral Component Interconnect Express(PCIe) throughput with four Graphics Processing Unit(GPU) memory managed mechanisms. By combining results from the architecture characterization with the Roofline Model based solely on architectural specification, this work offers insights for performance prediction of current and future architectures and their software systems. To that end, we instrument three applications and plot their resultant performance on the corresponding Roofline Model when run on a Blue Gene/Q architecture

High Performance Embedded Computing

Nowadays, the prevalence of computing systems in our lives is so ubiquitous that we live in a cyber-physical world dominated by computer systems, from pacemakers to cars and airplanes. These systems demand for more computational performance to process large amounts of data from multiple data sources with guaranteed processing times. Actuating outside of the required timing bounds may cause the failure of the system, being vital for systems like planes, cars, business monitoring, e-trading, etc. High-Performance and Time-Predictable Embedded Computing presents recent advances in software architecture and tools to support such complex systems, enabling the design of embedded computing devices which are able to deliver high-performance whilst guaranteeing the application required timing bounds. Technical topics discussed in the book include: Parallel embedded platforms Programming models Mapping and scheduling of parallel computations Timing and schedulability analysis Runtimes and operating systemsThe work reflected in this book was done in the scope of the European project P SOCRATES, funded under the FP7 framework program of the European Commission. High-performance and time-predictable embedded computing is ideal for personnel in computer/communication/embedded industries as well as academic staff and master/research students in computer science, embedded systems, cyber-physical systems and internet-of-things