Yves Robert

• Professor (Full) at École Normale Supérieure de Lyon

As real-time systems are safety critical, guaranteeing a high reliability threshold is as important as meeting all deadlines. Periodic tasks are replicated to mitigate the negative impact of transient faults, which leads to redundancy and high energy consumption. On the other hand, energy saving is widely identified as increasingly relevant issues...

After a machine failure, batch schedulers typically re‐schedule the job that failed with a high priority. This is fair for the failed job but still requires that job to re‐enter the submission queue and to wait for enough resources to become available. The waiting time can be very long when the job is large and the platform highly loaded, as is the...

This paper studies checkpointing strategies for parallel applications subject to failures. The optimal strategy to minimize total execution time, or makespan, is well known when failure IATs obey an Exponential distribution, but it is unknown for non-memoryless failure distributions. We explain why the latter fact is misunderstood in recent literat...

This work introduces scheduling algorithms to maximize the expected number of independent tasks that can be executed on a parallel platform within a given budget and under a deadline constraint. The main motivation for this problem comes from imprecise computations, where each job has a mandatory part and an optional part, and the objective is to m...

This paper revisits checkpointing strategies when workflows composed of multiple tasks execute on a parallel platform. The objective is to minimize the expectation of the total execution time. For a single task, the Young/Daly formula provides the optimal checkpointing period. However, when many tasks execute simultaneously, the risk that one of th...

This paper introduces and assesses novel strategies to schedule firm semi-periodic real-time tasks. Jobs are released periodically and have the same relative deadline. Job execution times obey an arbitrary probability distribution and can take either bounded or unbounded values. We investigate several optimization criteria, the most prominent being...

This paper revisits distributed termination detection algorithms in the context of High-Performance Computing (HPC) applications. We introduce an efficient variant of the Credit Distribution Algorithm (CDA) and compare it to the original algorithm (HCDA) as well as to its two primary competitors: the Four Counters algorithm (4C) and the Efficient D...

We study the resilient scheduling of moldable parallel jobs on high-performance computing (HPC) platforms. Moldable jobs allow for choosing a processor allocation before execution, and their execution time obeys various speedup models. The objective is to minimize the overall completion time or the makespan, when jobs can fail due to silent errors...

This work provides an optimal checkpointing strategy to protect iterative applications from fail-stop errors. The application repeats the same execution pattern by executing consecutive iterations, and each iteration is composed of several tasks having different execution lengths and different checkpoint costs. There are n tasks; task $a_{i}$ , w...

This paper compares several fault-tolerance methods for the detection and correction of floating-point errors in matrix-matrix multiplication. These methods include replication, triplication, Algorithm-Based Fault Tolerance (ABFT) and residual checking (RC). Error correction for ABFT can be achieved either by solving a small-size linear system of e...

This paper focuses on the resilient scheduling of parallel jobs on high-performance computing (HPC) platforms to minimize the overall completion time, or the makespan. We revisit the classical problem while assuming that jobs are subject to failures caused by transient or silent errors, and hence may need to be re-executed each time they fail to co...

This work focuses on dynamic DAG scheduling under memory constraints. We target a shared-memory platform equipped with $p$ parallel processors. The goal is to bound the maximum amount of memory that may be needed by any schedule using p processors to execute the DAG. We refine the classical model that computes maximum cuts by introducing two types...

This paper introduces several budget‐aware algorithms to deploy scientific workflows on Infrastructure as a Service Cloud platforms, where users can request Virtual Machines (VMs) of different types, each with specific cost and computing resources. We use a realistic application/platform model with stochastic task weights, and VMs communicating thr...

This paper revisits replication coupled with checkpointing for fail-stop errors. Replication enables the application to survive many fail-stop errors, thereby allowing for longer checkpointing periods. Previously published works use replication with the no-restart strategy, which works as follows: (i) compute the application Mean Time To Interrupti...

This work deals with scheduling and checkpointing strategies to execute scientific workflows on failure-prone large-scale platforms. To the best of our knowledge, this work is the first to target fail-stop errors for arbitrary workflows. Most previous work addresses soft errors, which corrupt the task being executed by a processor but do not cause...

This article discusses scheduling strategies for the problem of maximizing the expected number of tasks that can be executed on a cloud platform within a given budget and under a deadline constraint. The execution times of tasks follow independent and identically distributed probability laws. The main questions are how many processors to enroll and...

Dense tensor decompositions have been widely used in many signal processing problems including analyzing speech signals, identifying the localization of signal sources, and many other communication applications. Computing these decompositions poses major computational challenges for big datasets emerging in these domains. CANDECOMP/PARAFAC (CP) and...

With the recent advent of many-core architectures such as chip multiprocessors (CMPs), the number of processing units accessing a global shared memory is constantly increasing. Co-scheduling techniques are used to improve application throughput on such architectures, but sharing resources often generates critical interferences. In this article, we...

This paper compares the performance of different approaches to tolerate failures for applications executing on large-scale failure-prone platforms. We study (i) Rigid applications, which use a constant number of processors throughout execution; (ii) Moldable applications, which can use a different number of processors after each restart following a...

Input/output (I/O) from various sources often contend for scarcely available bandwidth. For example, checkpoint/restart (CR) protocols can help to ensure application progress in failure-prone environments. However, CR I/O alongside an application's normal, requisite I/O can increase I/O contention and might negatively impact performance. In this wo...

Large-scale platforms currently experience errors from two di?erent sources, namely fail-stop errors (which interrupt the execution) and silent errors (which strike unnoticed and corrupt data). This work combines checkpointing and replication for the reliable execution of linear work?ows on platforms subject to these two error types. While checkpoi...

This paper compares the performance of different approaches to tolerate failures using checkpoint/restart when executed on large-scale failure-prone platforms. We study (i) \(\textsc {Rigid}\) applications, which use a constant number of processors throughout execution; (ii) \(\textsc {Moldable}\) applications, which can use a different number of p...

Parallel execution time is expected to decrease as the number of processors increases. We show in this chapter that this is not as easy as it seems, even for perfectly parallel applications. In particular, processors are subject to faults. The more processors are available, the more likely faults will strike during execution. The main strategy to c...

This work presents a realistic performance model to execute scientific workflows on high-bandwidth-memory architectures such as the Intel Knights Landing. We provide a detailed analysis of the execution time on such platforms, taking into account transfers from both fast and slow memory and their overlap with computations. We discuss several schedu...

This work deals with scheduling and checkpointing strategies to execute scientific workflows on failure-prone large-scale platforms. To the best of our knowledge, this work is the first to target fail-stop errors for arbitrary workflows. Most previous work addresses soft errors, which corrupt the task being executed by a processor but do not cause...

This paper provides a model and an analytical study of replication as a technique to cope with silent errors, as well as a mixture of both silent and fail-stop errors on large-scale platforms. Compared with fail-stop errors that are immediately detected when they occur, silent errors require a detection mechanism. To detect silent errors, many appl...

Applications structured as Directed Acyclic Graphs (DAGs) of tasks occur in many domains, including popular scientific workflows. DAG scheduling has thus received an enormous amount of attention. Many of the popular DAG scheduling heuristics make scheduling decisions based on path lengths. At large scale compute platforms are subject to various typ...

We consider the problem of orchestrating the execution of workflow applications structured as Directed Acyclic Graphs (DAGs) on parallel computing platforms that are subject to fail-stop failures. The objective is to minimize expected overall execution time, or makespan. A solution to this problem consists of a schedule of the workflow tasks on the...

This paper presents a model and performance study for Algorithm-Based Focused Recovery (ABFR) applied to N-body computations, subject to latent errors. We make a detailed comparison with the classical Checkpoint/Restart (CR) approach. While the model applies to general frameworks, the performance study is limited to perfect binary trees, due to the...

This chapter describes a unified framework for the detection and correction of silent errors, which constitute a major threat for scientific applications at extreme-scale. We first motivate the problem and explain why checkpointing must be combined with some verification mechanism. Then we introduce a general-purpose technique based upon computatio...

Building an infrastructure for exascale applications requires, in addition to many other key components, a stable and efficient failure detector. This article describes the design and evaluation of a robust failure detector that can maintain and distribute the correct list of alive resources within proven and scalable bounds. The detection and dist...

Cache-partitioned architectures allow subsections of the shared last-level cache (LLC) to be exclusively reserved for some applications. This technique dramatically limits interactions between applications that are concurrently executing on a multicore machine. Consider n applications that execute concurrently, with the objective to minimize the ma...

This paper provides a model and an analytical study of replication as a technique to detect and correct silent errors. Although other detection techniques exist for HPC applications, based on algorithms (ABFT), invariant preservation or data analytics, replication remains the most transparent and least intrusive technique. We explore the right leve...

In this paper, we design and analyze strategies to replicate the execution of an application on two different platforms subject to failures, using checkpointing on a shared stable storage. We derive the optimal pattern size~$W$ for a periodic checkpointing strategy where both platforms concurrently try and execute $W$ units of work before checkpoin...

Recently, the benefits of co-scheduling several applications have been demonstrated in a fault-free context, both in terms of performance and energy savings. However, large-scale computer systems are confronted by frequent failures, and resilience techniques must be employed for large applications to execute efficiently. Indeed, failures may create...

We focus on High Performance Computing (HPC) workflows whose dependency graph forms a linear chain, and we extend single-level checkpointing in two important directions. Our first contribution targets silent errors, and combines in-memory checkpoints with both partial and guaranteed verifications. Our second contribution deals with multi-level chec...

The objective of the PULSAR project was to design a programming model suitable for largescale machines with complex memory hierarchies, and to deliver a prototype implementation of a runtime system supporting that model. PULSAR tackled the challenge by proposing a programming model based on systolic processing and virtualization. The PULSAR program...

We provide a framework to analyze multi-level checkpointing protocols, by formally defining a k-level checkpointing pattern. We provide a first-order approximation to the P optimal checkpointing period, and show that the corresponding overhead is in the order of k '=1 p 2'C', where ' is the error rate at level ', and C' the checkpointing cost at le...

We consider algorithms for going from a "full" matrix to a condensed "band bidiagonal" form using orthogonal transformations. We use the framework of "algorithms by tiles". Within this framework, we study: (i) the tiled bidiagonalization algorithm BiDiag, which is a tiled version of the standard scalar bidiagonalization algorithm; and (ii) the R-bi...

In this article, we combine the traditional checkpointing and rollback recovery strategies with verification mechanisms to cope with both fail-stop and silent errors. The objective is to minimize makespan and/or energy consumption. For divisible load applications, we use first-order approximations to find the optimal checkpointing period to minimiz...

Many methods are available to detect silent errors in high-performance computing (HPC) applications. Each method comes with a cost, a recall (fraction of all errors that are actually detected, i.e., false negatives), and a precision (fraction of true errors amongst all detected errors, i.e., false positives). The main contribution of this paper is...

We study the scheduling of computational workflows on compute resources that experience exponentially distributed failures. When a failure occurs, rollback and recovery is used to resume the execution from the last checkpointed state. The scheduling problem is to minimize the expected execution time by deciding in which order to execute the tasks i...

The traditional single-level checkpointing method suffers from significant overhead on large-scale platforms. Hence, multilevel checkpointing protocols have been studied extensively in recent years. The multilevel checkpoint approach allows different levels of checkpoints to be set (each with different checkpoint overheads and recovery abilities),...

We consider techniques to improve the performance of parallel sparse triangular solution on non-uniform memory architecture multicores by extending earlier coloring and level set schemes for single-core multiprocessors. We develop STS-k, where k represents a small number of transformations for latency reduction from increased spatial and temporal l...

Several recent papers have introduced a periodic verification mechanism to detect silent errors in iterative solvers. Chen [PPoPP'13, pp. 167--176] has shown how to combine such a verification mechanism (a stability test checking the orthogonality of two vectors and recomputing the residual) with checkpointing: the idea is to verify every $d$ itera...

Several recent papers have introduced a periodic verification mechanism to detect silent errors in iterative solvers. Chen [PPoPP'13, pp. 167--176] has shown how to combine such a verification mechanism (a stability test checking the orthogonality of two vectors and recomputing the residual) with checkpointing: the idea is to verify every $d$ itera...

The classical redistribution problem aims at optimally scheduling communications when reshuffling from an initial data distribution to a target data distribution. This target data distribution is usually chosen to optimize some objective for the algorithmic kernel under study (good computational balance or low communication volume or cost), and the...

This work focuses on resilience techniques at extreme scale. Many papers dealwith fail-stop errors. Many others dealwith silent errors (or silent data corruptions).But very few papers deal with fail-stop and silent errorssimultaneously. However, HPC applications will obviously have to cope with both error sources.This paper presents a unified frame...

Fail-stop and silent errors are unavoidable on large-scale platforms. Efficient resiliencetechniques must accommodate both error sources. A traditional checkpointing and rollbackrecovery approach can be used, with added verifications to detect silent errors. A fail-stoperror leads to the loss of the whole memory content, hence the obligation to che...

Recently, the benefits of co-scheduling several applications have been demonstrated in a fault-free context, both in terms of performance and energy savings. However, large-scale computer systems are confronted to frequent failures, and resilience techniques must be employed to ensure the completion of large applications. Indeed, failures may creat...

We consider techniques to improve the performance of parallel sparse triangular solution on non-uniform memory architecture multicores by extending earlier coloring and level set schemes for single-core multiprocessors. We develop sts-k, where k represents a small number of transformations for latency reduction from increased spatial and temporal l...

Errors have become a critical problem for high-performance computing. Checkpointing protocols are often used for error recovery after fail-stop failures. However, silent errors cannot be ignored, and their peculiarity is that such errors are identified only when the corrupted data is activated. To cope with silent errors, we need a verification mec...

In this paper, we discuss several scheduling algorithms to execute independent tasks with voltage overscaling algorithms. Given a frequency to execute the tasks, operating at a voltage below threshold leads to significant energy savings but also induces timing errors. A verification mechanism must be enforced to detect these errors. Contrarily to f...