On the Reliability Assessment of Artificial Neural Networks Running on AI-Oriented MPSoCs

Nowadays, the usage of electronic devices running artificial neural networks (ANNs)-based applications is spreading in our everyday life. Due to their outstanding computational capabilities, ANNs have become appealing solutions for safety-critical systems as well. Frequently, they are considered intrinsically robust and fault tolerant for being brain-inspired and redundant computing models. However, when ANNs are deployed on resource-constrained hardware devices, single physical faults may compromise the activity of multiple neurons. Therefore, it is crucial to assess the reliability of the entire neural computing system, including both the software and the hardware components. This article systematically addresses reliability concerns for ANNs running on multiprocessor system-on-a-chips (MPSoCs). It presents a methodology to assign resilience scores to individual neurons and, based on that, schedule the workload of an ANN on the target MPSoC so that critical neurons are neatly distributed among the available processing elements. This reliability-oriented methodology exploits an integer linear programming solver to find the optimal solution. Experimental results are given for three different convolutional neural networks trained on MNIST, SVHN, and CIFAR-10. We carried out a comprehensive assessment on an open-source artificial intelligence-based RISC-V MPSoC. The results show the reliability improvements of the proposed methodology against the traditional scheduling

Reliability and Security Assessment of Modern Embedded Devices

L'abstract è presente nell'allegato / the abstract is in the attachmen

Fixed-Order Scheduling on Parallel Machines

We consider the following natural scheduling problem: Given a sequence of jobs with weights and processing times, one needs to assign each job to one of m identical machines in order to minimize the sum of weighted completion times. The twist is that for machine the jobs assigned to it must obey the order of the input sequence, as is the case in multi-server queuing systems. We establish a constant factor approximation algorithm for this (strongly NP-hard) problem. Our approach is necessarily very different from what has been used for similar scheduling problems without the fixed-order assumption. We also give a QPTAS for the special case of unit processing times

Fixed-order scheduling on parallel machines

We consider the following natural scheduling problem: Given a sequence of jobs with weights and processing times, one needs to assign each job to one of m identical machines in order to minimize the sum of weighted completion times. The twist is that for machine the jobs assigned to it must obey the order of the input sequence, as is the case in multi-server queuing systems. We establish a constant factor approximation algorithm for this (strongly NP-hard) problem. Our approach is necessarily very different from what has been used for similar scheduling problems without the fixed-order assumption. We also give a QPTAS for the special case of unit processing time

Integer Programming and Combinatorial Optimization [electronic resource] : 20th International Conference, IPCO 2019, Ann Arbor, MI, USA, May 22-24, 2019, Proceedings /

This book constitutes the refereed proceedings of the 20th International Conference on Integer Programming and Combinatorial Optimization, IPCO 2019, held in Ann Arbor, MI, USA, in May 2019. The 33 full versions of extended abstracts presented were carefully reviewed and selected from 114 submissions. The conference is a forum for researchers and practitioners working on various aspects of integer programming and combinatorial optimization. The aim is to present recent developments in theory, computation, and applications in these areas.Identically Self-Blocking Clutters -- Min-Max Correlation Clustering via -- Strong Mixed-Integer Programming Formulations for Trained Neural -- Extended Formulations from Communication Protocols in Output-Efficient -- Sub-Symmetry-Breaking Inequalities for ILP with Structured Symmetry -- Intersection Cuts for Polynomial Optimization -- Fixed-Order Scheduling on Parallel Machines -- Online Submodular Maximization: Beating 1/2 Made Simple -- Improving the Integrality Gap for Multiway Cut -- nell 1-sparsity Approximation Bounds for Packing Integer Programs -- A General Framework for Handling Commitment in Online Throughput Maximization -- Lower Bounds and A New Exact Approach for the Bilevel Knapsack with Interdiction Constraints -- On Friedmann's Subexponential Lower Bound for Zadeh's Pivot Rule -- Tight Approximation Ratio for Minimum Maximal Matching -- Integer Programming and Incidence Treedepth -- A Bundle Approach for SDPs with Exact Subgraph Constraints -- Dynamic Flows with Adaptive Route Choice -- The Markovian Price of Information -- On Perturbation Spaces of Minimal Valid Functions: Inverse Semigroup Theory and Equivariant Decomposition Theorem -- On Compact Representations of Voronoi Cells of Lattices -- An Efficient Characterization of Submodular Spanning Tree Games -- The Asymmetric Traveling Salesman Path LP Has Constant Integrality Ratio -- Approximate Multi-Matroid Intersection via Iterative Refinement -- An Exact Algorithm for Robust Influence Maximization -- A New Contraction Technique with Applications to Congruency-Constrained Cuts -- Sparsity of Integer Solutions in the Average Case -- A Generic Exact Solver for Vehicle Routing and Related Problems -- Earliest Arrival Transshipments in Networks With Multiple Sinks -- Intersection Cuts for Factorable MINLP -- Linear Programming Using Limited-Precision Oracles -- Computing the Nucleolus of Weighted Cooperative Matching Games in Polynomial Time -- Breaking Symmetries to Rescue SoS: The Case of Makespan Scheduling -- Random Projections for Quadratic Programs over a Euclidean Ball.This book constitutes the refereed proceedings of the 20th International Conference on Integer Programming and Combinatorial Optimization, IPCO 2019, held in Ann Arbor, MI, USA, in May 2019. The 33 full versions of extended abstracts presented were carefully reviewed and selected from 114 submissions. The conference is a forum for researchers and practitioners working on various aspects of integer programming and combinatorial optimization. The aim is to present recent developments in theory, computation, and applications in these areas