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Section: New Results

Language Based Fault-Tolerance

Participants : Dmitry Burlyaev, Pascal Fradet, Alain Girault, Yoann Geoffroy, Gregor Goessler, Jean-Bernard Stefani, Atena Abdi, Ismail Assayad.

Fault Ascription in Concurrent Systems

The failure of one component may entail a cascade of failures in other components; several components may also fail independently. In such cases, elucidating the exact scenario that led to the failure is a complex and tedious task that requires significant expertise.

The notion of causality (did an event e cause an event e'?) has been studied in many disciplines, including philosophy, logic, statistics, and law. The definitions of causality studied in these disciplines usually amount to variants of the counterfactual test “e is a cause of e' if both e and e' have occurred, and in a world that is as close as possible to the actual world but where e does not occur, e' does not occur either”. In computer science, almost all definitions of logical causality — including the landmark definition of [70] and its derivatives — rely on a causal model that may not be known, for instance in presence of black-box components. For such systems, we have been developing a framework for blaming that helps us establish the causal relationship between component failures and system failures, given an observed system execution trace. The analysis is based on a formalization of counterfactual reasoning [7] .

We have instantiated our approach to a synchronous data flow framework defined by a subset of the Lustre [69] language, and implemented the analysis in LoCA (see Section  6.2 ).

In [25] we have shown that we can improve precision of the analysis if (1) we can emulate execution of components instead of relying on their specifications, and (2) take into consideration input/output dependencies between components to avoid blaming components for faults induced by other components. We have demonstrated the utility of the extended analysis with a case study for a closed-loop patient-controlled analgesia system.

We have further proposed in [23] a general semantic framework for fault ascription. Our framework relies on configuration structures to handle concurrent systems, partial and distributed observations in a uniform way. It defines basic conditions for a counterfactual analysis of necessary and sufficient causes, and it presents a refined analysis that conforms to our basic conditions while avoiding various infelicities.

Tradeoff exploration between energy consumption and execution time

We have continued our work on multi-criteria scheduling, in two directions. First, in the context of dynamic applications that are launched and terminated on an embedded homogeneous multi-core chip, under execution time and energy consumption constraints, we have proposed a two layer adaptive scheduling method. In the first layer, each application (represented as a DAG of tasks) is scheduled statically on subsets of cores: 2 cores, 3 cores, 4 cores, and so on. For each size of these sets (2, 3, 4, ...), there may be only one topology or several topologies. For instance, for 2 or 3 cores there is only one topology (a “line”), while for 4 cores there are three distinct topologies (“line”, “square”, and “T shape”). Moreover, for each topology, we generate statically several schedules, each one subject to a different total energy consumption constraint, and consequently with a different Worst-Case Reaction Time (WCRT). Coping with the energy consumption constraints is achieved thanks to Dynamic Frequency and Voltage Scaling (DVFS). In the second layer, we use these pre-generated static schedules to reconfigure dynamically the applications running on the multi-core each time a new application is launched or an existing one is stopped. The goal of the second layer is to perform a dynamic global optimization of the configuration, such that each running application meets a pre-defined quality-of-service constraint (translated into an upper bound on its WCRT) and such that the total energy consumption be minimized. For this, we (1) allocate a sufficient number of cores to each active application, (2) allocate the unassigned cores to the applications yielding the largest gain in energy, and (3) choose for each application the best topology for its subset of cores (i.e., better than the by default “line” topology). This is a joint work with Ismail Assayad (U. Casablanca, Morocco) who visited the team in September 2015.

Second, in the context of a static application (again represented a DAG of tasks) running on an homogeneous multi-core chip, we have worked on the static scheduling minimizing the WCRT of the application under the multiple constraints that the reliability, the power consumption, and the temperature remain below some given threshold. There are multiple difficulties: (1) the reliability is not an invariant measure w.r.t. time, which makes it impossible to use backtrack-free scheduling algorithms such as list scheduling [37] ; to overcome this, we adopt instead the Global System Failure Rate (GSFR) as a measure of the system's reliability that is invariant with time [64] ; (2) keeping the power consumption under a given threshold requires to lower the voltage and frequency, but this has a negative impact both on the WCRT and on the GSFR; keeping the GSFR below a given threshold requires to replicate the tasks on multiple cores, but this has a negative impact both on the WCRT, on the power consumption, and on the temperature; (3) keeping the temperature below a given threshold is even more difficult because the temperature continues to increase even after the activity stops, so each scheduling decision must be assessed not based on the current state of the chip (i.e., the temperature of each core) but on the state of the chip at the end of the candidate task, and cooling slacks must be inserted. This is a joint work with Atena Abdi (Amirkabir U., Iran) who is a PhD visitor in the team.

Automatic transformations for fault tolerant circuits

In the past years, we have studied the implementation of specific fault tolerance techniques in real-time embedded systems using program transformation [1] . We are now investigating the use of automatic transformations to ensure fault-tolerance properties in digital circuits. To this aim, we consider program transformations for hardware description languages (HDL). We consider both single-event upsets (SEU) and single-event transients (SET) and fault models of the form “at most 1 SEU or SET within n clock cycles”.

We have proposed novel fault-tolerance transformations based on time-redundancy. In particular, we have presented a transformation using double-time redundancy (DTR) coupled with micro-checkpointing, rollback and a speedup mode [19] . The approach is capable to mask any SET every 10 cycles and keeps the same input/output behavior regardless error occurrences. Usually transparent masking requires triple redundancy and voting. Experimental results on the ITC'99 benchmark suite indicate that the hardware overhead of DTR is 2.7 to 6.1 times smaller than full TMR with a double loss in throughput. The method does not require any specific hardware support and is an interesting alternative to Triple Modular Redundancy (TMR) for logic intensive designs.

We have also designed a transformation that allows the circuit to change its level of time-redundancy. This feature allows the circuit to dynamically and temporarily lower (resp. increase) fault-tolerance and speed up (resp. slow down) its computation without interruption [20] . The motivations for such changes can be based on the current radiation environment or the processing of critical data. When hardware size is limited and fault-tolerance is only occasionally needed, that scheme is a better choice than static TMR, which involves a constant high area overhead

These time redundancy transformations (DTR and adaptive fault-tolerance) have been patented [50]

We have described how to formally certify fault-tolerant transformations using the Coq proof assistant [53] (see Section  6.3 ). The transformations are described on a simple gate-level hardware description language LDDL (Low-level Dependent Description Language). This combinator language is equiped with dependent types and ensures that circuits are well-formed by construction (gates correctly plugged, no dangling wires, no combinational loops, ...). Fault-models are specified in the operational semantics of the language. The main theorem states that, for any circuit, for any input stream and for any SET allowed by the fault-model, its transformed version produces a correct output [18] . The primary motivation of this work was to certify DTR whose intricacy requested a formal proof to make sure that no single-point of failure existed. We have first applied this approach to the correctness proofs of TMR, TTR (Triple Time Redundancy) and finally DTR.

This research is part of Dmitry Burlyaev's pHD thesis [11] defended in November 2015.

A formal approach for the synthesis and implementation of fault-tolerant embedded systems

We have been working for several years on the usage of discrete controller synthesis (DCS) [83] to provide the automated addition of fault-tolerance in embedded systems with formal guarantees [65] . The first key idea is that the initial system model (usually an LTS) includes both the expected behaviors, the unexpected ones (that is, the failures), and the reconfigurations (typically repair actions). The second key idea is that the failures are modeled as uncontrollable events. Then, thanks to an exhaustive state space traversal, DCS is able to generate a controller that will prevent the system from entering a “bad” state (e.g., a configuration of the system where a task is active on a faulty processor). From the point of view of fault-tolerance, this approach combines the advantages of static guarantees with that of dynamic reconfiguration (hence without the penalty of static redundancy).

Through this new work, we have demonstrated the feasibility of a complete workflow to synthesize and implement correct-by-construction fault tolerant distributed embedded systems consisting of real-time periodic tasks [24] . Correct-by-construction is provided by the use of DCS, which allows us to guarantee that the synthesized controlled system guarantees the functionality of its tasks even in the presence of processor failures. For this step, our workflow uses the Heptagon domain specific language [58] and the Sigali DCS tool [79] . The correct implementation of the resulting distributed system is a challenge, all the more since the controller itself must be tolerant to the processor failures. We achieve this step thanks to the libDGALS real-time library [89] (1) to generate the glue code that will migrate the tasks upon processor failures, maintaining their internal state through migration, and (2) to make the synthesized controller itself fault-tolerant.