Renaud Sirdey

Recent Advances in Homomorphic Encryption: A Possible Future for Signal Processing in the Encrypted Domain

Since the introduction of the notion of privacy homomorphism by Rivest et al. in the late 1970s, the design of efficient and secure encryption schemes allowing the performance of general computations in the encrypted domain has been one of the holy grails of the cryptographic community. Despite numerous partial answers, the problem of designing such a powerful primitive has remained open until the theoretical breakthrough of the fully homomorphic encryption (FHE) scheme published by Gentry in the late 2000s. Since then, progress has been fast-paced, and it can now be reasonably said that practical homomorphic encryption-based computing will become a reality in the near future.

ΣC: a programming model and language for embedded manycores

We present ΣC, a programming model and language for high performance embedded manycores. The programming model is based on process networks with non determinism extensions and process behavior specifications. The language itself extends C, with parallelism, composition and process abstractions. It is intended to support architecture independent, high-level parallel programming on embedded manycores, and allows for both low execution overhead and strong execution guarantees. ΣC is being developed as part of an industry-grade tool chain for a high performance embedded manycore architecture.

Minimizing Task Preemptions and Migrations in Multiprocessor Optimal Real-Time Schedules

We present a new approach to decrease task preemptions and migrations in optimal global real-time schedules on symmetric multiprocessors. Contrary to classical approaches, our method proceeds in two steps, one off-line to place jobs on intervals and one on-line to schedule them dynamically inside each interval. We propose a new linear programming formulation and a local scheduler which exhibits low complexity and produces few task preemptions and migrations. We compare our approach with other optimal scheduling algorithms, using the implicit-deadline periodic task model. Simulation results illustrate the competitiveness of our approach with respect to task preemptions and migrations.

Towards Practical Program Execution over Fully Homomorphic Encryption Schemes

This paper intends to provide a first assessment of the practicality of using Fully Homomorphic Encryption (FHE) to perform real calculations, in terms of software engineering as well as performances. We present a prototype of a compilation and execution infrastructure targeting any FHE scheme. The paper also provides some preliminary experimental results obtained with our implementation of the Brakerski-Gentry-Vaikuntanathan (BGV) scheme, which is one of the most promising FHE schemes with respect to practicality.

On a resource-constrained scheduling problem with application to distributed systems reconfiguration

This paper is devoted to the study of a resource-constrained scheduling problem, the Process Move Programming problem, which arises in relation to the operability of certain high availability real-time distributed systems. Informally, this problem consists, starting from an arbitrary initial distribution of processes on the processors of a distributed system, in finding the least disruptive sequence of operations (non-impacting process migrations or temporary process interruptions) at the end of which the system ends up in another predefined arbitrary state. The main constraint is that the capacity of the processors must not be exceeded during the reconfiguration. After a brief survey of the literature, we prove the NP-hardness of the problem and exhibit a few polynomial special cases. We then present a branch-and-bound algorithm for the general case along with computational results demonstrating its practical relevance. The paper is concluded by a discussion on further research.

Armadillo: A Compilation Chain for Privacy Preserving Applications

In this work we present Armadillo a compilation chain used for compiling applications written in a high-level language (C++) to work on encrypted data. The back-end of the compilation chain is based on homomorphic encryption. The tool-chain further automatically handle a huge amount of parallelism so as to mitigate the performance overhead of using homomorphic encryption.

Two-stage hybrid flow shop with precedence constraints and parallel machines at second stage

This study deals with the two-stage hybrid flow shop (HFS) problem with precedence constraints. Two versions are examined, the classical HFS where idle time between the operations of the same job is allowed and the no-wait HFS where idle time is not permitted. For solving these problems an adaptive randomized list scheduling heuristic is proposed. Two global bounds are also introduced so as to conservatively estimate the distance to optimality of the proposed heuristic. The evaluation is done on a set of randomly generated instances. The heuristic solutions for the classical HFS in average are provably situated below 2% from the optimal ones, and on the other hand, in the case of the no-wait HFS the average deviation is below 5%. Highlights? We study the hybrid flow shop problem with precedence relations. ? An adaptive randomized list scheduling heuristic is proposed. ? Two global lower bounds are examined. ? Distance to the optimum, in average, is under 5% for randomly generated instances.

A Parallel Simulated Annealing Approach for the Mapping of Large Process Networks

We propose a parallel simulated annealing approach to solve a dataflow process network mapping problem, where a network of communicating tasks is mapped into a set of processors with limited resource capacities, while minimizing the overall communication bandwidth between processors. The speedups obtained using this approach enables us to solve problems with more than one thousand tasks, on up to 48 processors, in reasonable time. Results have been obtained by taking profit of the specific architecture of a Non-Uniform Memory Access (NUMA) computer.

Throughput Constrained Parallelism Reduction in Cyclo-static Dataflow Applications

Abstract This paper deals with semantics-preserving parallelism reduction methods for cyclo-static dataflow applications. Parallelism reduction is the process of equivalent actors fusioning. The principal objectives of parallelism reduction are to decrease the memory footprint of an application and to increase its execution performance. We focus on parallelism reduction methodolo- gies constrained by application throughput. A generic parallelism reduction methodology is introduced. Experimental results are provided for asserting the performance of the proposed method.

Parallelism Reduction Based on Pattern Substitution in Dataflow Oriented Programming Languages

In this paper, we present a compiler extension for applications targeting high performance embedded systems. It analyzes the graph of a dataflow application in order to adapt its parallelism degree. Our approach consists in the detection and the substitution of built-in patterns in the dataflow. Modifications applied on the graph do not alter the semantic of the application. A parallelism reduction engine is also described to perform an exhaustive search of the best reduction. Our proposition has been implemented within an industry-grade compiler for the Sigma-C dataflow language. It shows that for dataflow applications, the parallelism reduction extension helps the user focus on the algorithm by hiding all parallelism tuning considerations. Experimentations demonstrate the accuracy and the performance of the reduction engine for both synthetic and real applications.