8 research outputs found
Node-Type-Based Load-Balancing Routing for Parallel Generalized Fat-Trees
High-Performance Computing (HPC) clusters are made up of a variety of node
types (usually compute, I/O, service, and GPGPU nodes) and applications don't
use nodes of a different type the same way. Resulting communication patterns
reflect organization of groups of nodes, and current optimal routing algorithms
for all-to-all patterns will not always maximize performance for group-specific
communications. Since application communication patterns are rarely available
beforehand, we choose to rely on node types as a good guess for node usage. We
provide a description of node type heterogeneity and analyse performance
degradation caused by unlucky repartition of nodes of the same type. We provide
an extension to routing algorithms for Parallel Generalized Fat-Tree topologies
(PGFTs) which balances load amongst groups of nodes of the same type. We show
how it removes these performance issues by comparing results in a variety of
situations against corresponding classical algorithms
High-Quality Fault-Resiliency in Fat-Tree Networks (Extended Abstract)
Coupling regular topologies with optimized routing algorithms is key in
pushing the performance of interconnection networks of HPC systems. In this
paper we present Dmodc, a fast deterministic routing algorithm for Parallel
Generalized Fat-Trees (PGFTs) which minimizes congestion risk even under
massive topology degradation caused by equipment failure. It applies a
modulo-based computation of forwarding tables among switches closer to the
destination, using only knowledge of subtrees for pre-modulo division. Dmodc
allows complete rerouting of topologies with tens of thousands of nodes in less
than a second, which greatly helps centralized fabric management react to
faults with high-quality routing tables and no impact to running applications
in current and future very large-scale HPC clusters. We compare Dmodc against
routing algorithms available in the InfiniBand control software (OpenSM) first
for routing execution time to show feasibility at scale, and then for
congestion risk under degradation to demonstrate robustness. The latter
comparison is done using static analysis of routing tables under random
permutation (RP), shift permutation (SP) and all-to-all (A2A) traffic patterns.
Results for Dmodc show A2A and RP congestion risks similar under heavy
degradation as the most stable algorithms compared, and near-optimal SP
congestion risk up to 1% of random degradation
Nouveaux algorithmes de routage pour supercalculateurs exaflopiques hétérogènes
Building efficient supercomputers requires optimising communications, and their exaflopic scale causes an unavoidable risk of relatively frequent failures.For a cluster with given networking capabilities and applications, performance is achieved by providing a good route for every message while minimising resource access conflicts between messages.This thesis focuses on the fat-tree family of networks, for which we define several overarching properties so as to efficiently take into account a realistic superset of this topology, while keeping a significant edge over agnostic methods.Additionally, a partially novel static congestion risk evaluation method is used to compare algorithms.A generic optimisation is presented for some applications on clusters with heterogeneous equipment.The proposed algorithms use distinct approaches to improve centralised static routing by combining computation speed, fault-resilience, and minimal congestion risk.La construction de supercalculateurs performants nécessite d'optimiser les communications, et leur échelle exaflopique amène un risque inévitable de pannes relativement fréquentes.Pour un cluster avec un réseau et des équipements donnés, on améliore les performances en s'assurant que l'on sélectionne une bonne route pour chaque message tout en minimisant les conflits d'accès aux resources entre messages.Cette thèse se concentre sur la famille des réseaux fat-trees, pour laquelle nous donnons quelques grandes caractéristiques afin de mieux prendre en compte une classe réaliste de cette topologie, tout en conservant un avantage par rapport aux méthodes agnostiques.De plus, une approche d'évaluation statique partiellement nouvelle du risque de congestion est utilisée pour comparer les algorithmes.Une optimisation générique est présentée pour certaines applications sur des clusters avec des équipements hétérogènes.Les algorithmes proposés forment le résultat de plusieurs approches distinctes pour apporter des contributions dans le domaine du routage statique centralisé, en combinant rapidité de calcul, résilience aux pannes, et minimisation du risque de congestion
Node-Type-Based Load-Balancing Routing for Parallel Generalized Fat-Trees
International audienceHigh-Performance Computing (HPC) clusters are made up of a variety of node types (usually compute, I/O, service, and GPGPU nodes) and applications don't use nodes of a different type the same way. Resulting communication patterns reflect organization of groups of nodes, and current optimal routing algorithms for all-to-all patterns will not always maximize performance for group-specific communications. Since application communication patterns are rarely available beforehand, we choose to rely on node types as a good guess for node usage. We provide a description of node type heterogeneity and analyse performance degradation caused by unlucky repartition of nodes of the same type. We provide an extension to routing algorithms for Parallel Generalized Fat-Tree topologies (PGFTs) which balances load amongst groups of nodes of the same type. We show how it removes these performance issues by comparing results in a variety of situations against corresponding classical algorithms
High-Quality Fault Resiliency in Fat Trees
International audienceCoupling regular topologies with optimised routing algorithms is key in pushing the performance of interconnection networks of supercomputers.In this paper we present Dmodc, a fast deterministic routing algorithm for Parallel Generalised Fat-Trees (PGFTs) which minimises congestion risk even under massive network degradation caused by equipment failure.Dmodc computes forwarding tables with a closed-form arithmetic formula by relying on a fast preprocessing phase.This allows complete re-routing of networks with tens of thousands of nodes in less than a second.In turn, this greatly helps centralised fabric management react to faults with high-quality routing tables and no impact to running applications in current and future very large-scale HPC clusters
High-Quality Fault-Resiliency in Fat-Tree Networks (Extended Abstract)
International audienceCoupling regular topologies with optimized routing algorithms is key in pushing the performance of interconnection networks of HPC systems. In this paper we present Dmodc, a fast deterministic routing algorithm for Parallel Generalized Fat-Trees (PGFTs) which minimizes congestion risk even under massive topology degradation caused by equipment failure. It applies a modulo-based computation of forwarding tables among switches closer to the destination, using only knowledge of subtrees for pre-modulo division. Dmodc allows complete rerouting of topologies with tens of thousands of nodes in less than a second, which greatly helps centralized fabric management react to faults with high-quality routing tables and no impact to running applications in current and future very large-scale HPC clusters. We compare Dmodc against routing algorithms available in the InfiniBand control software (OpenSM) first for routing execution time to show feasibility at scale, and then for congestion risk under degradation to demonstrate robustness. The latter comparison is done using static analysis of routing tables under random permutation (RP), shift permutation (SP) and all-to-all (A2A) traffic patterns. Results for Dmodc show A2A and RP congestion risks similar under heavy degradation as the most stable algorithms compared, and near-optimal SP congestion risk up to 1% of random degradation