New Techniques to Reduce the Execution Time of Functional Test Programs

The compaction of test programs for processor-based systems is of utmost practical importance: Software-Based Self-Test (SBST) is nowadays increasingly adopted, especially for in-field test of safety-critical applications, and both the size and the execution time of the test are critical parameters. However, while compacting the size of binary test sequences has been thoroughly studied over the years, the reduction of the execution time of test programs is still a rather unexplored area of research. This paper describes a family of algorithms able to automatically enhance an existing test program, reducing the time required to run it and, as a side effect, its size. The proposed solutions are based on instruction removal and restoration, which is shown to be computationally more efficient than instruction removal alone. Experimental results demonstrate the compaction capabilities, and allow analyzing computational costs and effectiveness of the different algorithms

Innovative Techniques for Testing and Diagnosing SoCs

We rely upon the continued functioning of many electronic devices for our everyday welfare, usually embedding integrated circuits that are becoming even cheaper and smaller with improved features. Nowadays, microelectronics can integrate a working computer with CPU, memories, and even GPUs on a single die, namely System-On-Chip (SoC). SoCs are also employed on automotive safety-critical applications, but need to be tested thoroughly to comply with reliability standards, in particular the ISO26262 functional safety for road vehicles. The goal of this PhD. thesis is to improve SoC reliability by proposing innovative techniques for testing and diagnosing its internal modules: CPUs, memories, peripherals, and GPUs. The proposed approaches in the sequence appearing in this thesis are described as follows: 1. Embedded Memory Diagnosis: Memories are dense and complex circuits which are susceptible to design and manufacturing errors. Hence, it is important to understand the fault occurrence in the memory array. In practice, the logical and physical array representation differs due to an optimized design which adds enhancements to the device, namely scrambling. This part proposes an accurate memory diagnosis by showing the efforts of a software tool able to analyze test results, unscramble the memory array, map failing syndromes to cell locations, elaborate cumulative analysis, and elaborate a final fault model hypothesis. Several SRAM memory failing syndromes were analyzed as case studies gathered on an industrial automotive 32-bit SoC developed by STMicroelectronics. The tool displayed defects virtually, and results were confirmed by real photos taken from a microscope. 2. Functional Test Pattern Generation: The key for a successful test is the pattern applied to the device. They can be structural or functional; the former usually benefits from embedded test modules targeting manufacturing errors and is only effective before shipping the component to the client. The latter, on the other hand, can be applied during mission minimally impacting on performance but is penalized due to high generation time. However, functional test patterns may benefit for having different goals in functional mission mode. Part III of this PhD thesis proposes three different functional test pattern generation methods for CPU cores embedded in SoCs, targeting different test purposes, described as follows: a. Functional Stress Patterns: Are suitable for optimizing functional stress during I Operational-life Tests and Burn-in Screening for an optimal device reliability characterization b. Functional Power Hungry Patterns: Are suitable for determining functional peak power for strictly limiting the power of structural patterns during manufacturing tests, thus reducing premature device over-kill while delivering high test coverage c. Software-Based Self-Test Patterns: Combines the potentiality of structural patterns with functional ones, allowing its execution periodically during mission. In addition, an external hardware communicating with a devised SBST was proposed. It helps increasing in 3% the fault coverage by testing critical Hardly Functionally Testable Faults not covered by conventional SBST patterns. An automatic functional test pattern generation exploiting an evolutionary algorithm maximizing metrics related to stress, power, and fault coverage was employed in the above-mentioned approaches to quickly generate the desired patterns. The approaches were evaluated on two industrial cases developed by STMicroelectronics; 8051-based and a 32-bit Power Architecture SoCs. Results show that generation time was reduced upto 75% in comparison to older methodologies while increasing significantly the desired metrics. 3. Fault Injection in GPGPU: Fault injection mechanisms in semiconductor devices are suitable for generating structural patterns, testing and activating mitigation techniques, and validating robust hardware and software applications. GPGPUs are known for fast parallel computation used in high performance computing and advanced driver assistance where reliability is the key point. Moreover, GPGPU manufacturers do not provide design description code due to content secrecy. Therefore, commercial fault injectors using the GPGPU model is unfeasible, making radiation tests the only resource available, but are costly. In the last part of this thesis, we propose a software implemented fault injector able to inject bit-flip in memory elements of a real GPGPU. It exploits a software debugger tool and combines the C-CUDA grammar to wisely determine fault spots and apply bit-flip operations in program variables. The goal is to validate robust parallel algorithms by studying fault propagation or activating redundancy mechanisms they possibly embed. The effectiveness of the tool was evaluated on two robust applications: redundant parallel matrix multiplication and floating point Fast Fourier Transform

Massively Extended Modular Monitoring and a Second Life for Upper Stages

Launching science and technology experiments to space is expensive. Although commercial spaceflight has resulted in a drop of prices, the cost for a launch is still significant. However, most of theweight that is needed to conduct experiments in space belongs to the spacecraft’s bus and it is responsiblefor power distribution, thermal management, orbital control and communications. An upper stage, on the other hand, includes all the necessary subsystems andhas to be launched in any case. Many upper stages (e.g. ARIANE5) will even stay in orbit for severalyears after their nominal mission with all their subsystems intact but passivated.We proposea compact system based on a protective container and high-performance Commercial-off-the-Shelf (COTS) hardwarethat allows cost-efficient launching oftechnology experiments by reusing the launcher’s upper stage and its subsystems. Addingacquisition channels for various sensors gives the launch provider the ability to exploitthe computational power of the COTS hardwareduring the nominal mission. In contrast to existing systems,intelligent and mission-dependent data selection and compression can beapplied to the sensor data.In this paper, we demonstrate the implementation and qualification of a payload bussystem based on COTScomponentsthat is minimallyinvasive to the launcher(ARIANE5)and its nominal missionwhile offering computational power to both the launch provider and a potential payloaduser. The reliability of the COTS-based system is improvedby radiation hardening techniques and software-based self-test detecting and counteracting faults during the mission

New techniques for functional testing of microprocessor based systems

Electronic devices may be affected by failures, for example due to physical defects. These defects may be introduced during the manufacturing process, as well as during the normal operating life of the device due to aging. How to detect all these defects is not a trivial task, especially in complex systems such as processor cores. Nevertheless, safety-critical applications do not tolerate failures, this is the reason why testing such devices is needed so to guarantee a correct behavior at any time. Moreover, testing is a key parameter for assessing the quality of a manufactured product. Consolidated testing techniques are based on special Design for Testability (DfT) features added in the original design to facilitate test effectiveness. Design, integration, and usage of the available DfT for testing purposes are fully supported by commercial EDA tools, hence approaches based on DfT are the standard solutions adopted by silicon vendors for testing their devices. Tests exploiting the available DfT such as scan-chains manipulate the internal state of the system, differently to the normal functional mode, passing through unreachable configurations. Alternative solutions that do not violate such functional mode are defined as functional tests. In microprocessor based systems, functional testing techniques include software-based self-test (SBST), i.e., a piece of software (referred to as test program) which is uploaded in the system available memory and executed, with the purpose of exciting a specific part of the system and observing the effects of possible defects affecting it. SBST has been widely-studies by the research community for years, but its adoption by the industry is quite recent. My research activities have been mainly focused on the industrial perspective of SBST. The problem of providing an effective development flow and guidelines for integrating SBST in the available operating systems have been tackled and results have been provided on microprocessor based systems for the automotive domain. Remarkably, new algorithms have been also introduced with respect to state-of-the-art approaches, which can be systematically implemented to enrich SBST suites of test programs for modern microprocessor based systems. The proposed development flow and algorithms are being currently employed in real electronic control units for automotive products. Moreover, a special hardware infrastructure purposely embedded in modern devices for interconnecting the numerous on-board instruments has been interest of my research as well. This solution is known as reconfigurable scan networks (RSNs) and its practical adoption is growing fast as new standards have been created. Test and diagnosis methodologies have been proposed targeting specific RSN features, aimed at checking whether the reconfigurability of such networks has not been corrupted by defects and, in this case, at identifying the defective elements of the network. The contribution of my work in this field has also been included in the first suite of public-domain benchmark networks

New Techniques for On-line Testing and Fault Mitigation in GPUs

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

Energy-Efficient and Reliable Computing in Dark Silicon Era

Dark silicon denotes the phenomenon that, due to thermal and power constraints, the fraction of transistors that can operate at full frequency is decreasing in each technology generation. Moore’s law and Dennard scaling had been backed and coupled appropriately for five decades to bring commensurate exponential performance via single core and later muti-core design. However, recalculating Dennard scaling for recent small technology sizes shows that current ongoing multi-core growth is demanding exponential thermal design power to achieve linear performance increase. This process hits a power wall where raises the amount of dark or dim silicon on future multi/many-core chips more and more. Furthermore, from another perspective, by increasing the number of transistors on the area of a single chip and susceptibility to internal defects alongside aging phenomena, which also is exacerbated by high chip thermal density, monitoring and managing the chip reliability before and after its activation is becoming a necessity. The proposed approaches and experimental investigations in this thesis focus on two main tracks: 1) power awareness and 2) reliability awareness in dark silicon era, where later these two tracks will combine together. In the first track, the main goal is to increase the level of returns in terms of main important features in chip design, such as performance and throughput, while maximum power limit is honored. In fact, we show that by managing the power while having dark silicon, all the traditional benefits that could be achieved by proceeding in Moore’s law can be also achieved in the dark silicon era, however, with a lower amount. Via the track of reliability awareness in dark silicon era, we show that dark silicon can be considered as an opportunity to be exploited for different instances of benefits, namely life-time increase and online testing. We discuss how dark silicon can be exploited to guarantee the system lifetime to be above a certain target value and, furthermore, how dark silicon can be exploited to apply low cost non-intrusive online testing on the cores. After the demonstration of power and reliability awareness while having dark silicon, two approaches will be discussed as the case study where the power and reliability awareness are combined together. The first approach demonstrates how chip reliability can be used as a supplementary metric for power-reliability management. While the second approach provides a trade-off between workload performance and system reliability by simultaneously honoring the given power budget and target reliability

Fault Detection Methodology for Caches in Reliable Modern VLSI Microprocessors based on Instruction Set Architectures

Η παρούσα διδακτορική διατριβή εισάγει μία χαμηλού κόστους μεθοδολογία για την ανίχνευση ελαττωμάτων σε μικρές ενσωματωμένες κρυφές μνήμες που βασίζεται σε σύγχρονες Αρχιτεκτονικές Συνόλου Εντολών και εφαρμόζεται με λογισμικό αυτοδοκιμής. Η προτεινόμενη μεθοδολογία εφαρμόζει αλγορίθμους March μέσω λογισμικού για την ανίχνευση τόσο ελαττωμάτων αποθήκευσης όταν εφαρμόζεται σε κρυφές μνήμες που περιέχουν μόνο στατικές μνήμες τυχαίας προσπέλασης όπως για παράδειγμα κρυφές μνήμες επιπέδου 1, όσο και ελαττωμάτων σύγκρισης όταν εφαρμόζεται σε κρυφές μνήμες που περιέχουν εκτός από SRAM μνήμες και μνήμες διευθυνσιοδοτούμενες μέσω περιεχομένου, όπως για παράδειγμα πλήρως συσχετιστικές κρυφές μνήμες αναζήτησης μετάφρασης. Η προτεινόμενη μεθοδολογία εφαρμόζεται και στις τρεις οργανώσεις συσχετιστικότητας κρυφής μνήμης και είναι ανεξάρτητη της πολιτικής εγγραφής στο επόμενο επίπεδο της ιεραρχίας. Η μεθοδολογία αξιοποιεί υπάρχοντες ισχυρούς μηχανισμούς των μοντέρνων ISAs χρησιμοποιώντας ειδικές εντολές, που ονομάζονται στην παρούσα διατριβή Εντολές Άμεσης Προσπέλασης Κρυφής Μνήμης (Direct Cache Access Instructions - DCAs). Επιπλέον, η προτεινόμενη μεθοδολογία εκμεταλλεύεται τους έμφυτους μηχανισμούς καταγραφής απόδοσης και τους μηχανισμούς χειρισμού παγίδων που είναι διαθέσιμοι στους σύγχρονους επεξεργαστές. Επιπρόσθετα, η προτεινόμενη μεθοδολογία εφαρμόζει την λειτουργία σύγκρισης των αλγορίθμων March όταν αυτή απαιτείται (για μνήμες CAM) και επαληθεύει το αποτέλεσμα του ελέγχου μέσω σύντομης απόκρισης, ώστε να είναι συμβατή με τις απαιτήσεις του ελέγχου εντός λειτουργίας. Τέλος, στη διατριβή προτείνεται μία βελτιστοποίηση της μεθοδολογίας για πολυνηματικές, πολυπύρηνες αρχιτεκτονικές.The present PhD thesis introduces a low cost fault detection methodology for small embedded cache memories that is based on modern Instruction Set Architectures and is applied with Software-Based Self-Test (SBST) routines. The proposed methodology applies March tests through software to detect both storage faults when applied to caches that comprise Static Random Access Memories (SRAM) only, e.g. L1 caches, and comparison faults when applied to caches that apart from SRAM memories comprise Content Addressable Memories (CAM) too, e.g. Translation Lookaside Buffers (TLBs). The proposed methodology can be applied to all three cache associativity organizations: direct mapped, set-associative and full-associative and it does not depend on the cache write policy. The methodology leverages existing powerful mechanisms of modern ISAs by utilizing instructions that we call in this PhD thesis Direct Cache Access (DCA) instructions. Moreover, our methodology exploits the native performance monitoring hardware and the trap handling mechanisms which are available in modern microprocessors. Moreover, the proposed Methodology applies March compare operations when needed (for CAM arrays) and verifies the test result with a compact response to comply with periodic on-line testing needs. Finally, a multithreaded optimization of the proposed methodology that targets multithreaded, multicore architectures is also presented in this thesi

Study of Fine-Grained, Irregular Parallel Applications on a Many-Core Processor

This dissertation demonstrates the possibility of obtaining strong speedups for a variety of parallel applications versus the best serial and parallel implementations on commodity platforms. These results were obtained using the PRAM-inspired Explicit Multi-Threading (XMT) many-core computing platform, which is designed to efficiently support execution of both serial and parallel code and switching between the two. Biconnectivity: For finding the biconnected components of a graph, we demonstrate speedups of 9x to 33x on XMT relative to the best serial algorithm using a relatively modest silicon budget. Further evidence suggests that speedups of 21x to 48x are possible. For graph connectivity, we demonstrate that XMT outperforms two contemporary NVIDIA GPUs of similar or greater silicon area. Prior studies of parallel biconnectivity algorithms achieved at most a 4x speedup, but we could not find biconnectivity code for GPUs to compare biconnectivity against them. Triconnectivity: We present a parallel solution to the problem of determining the triconnected components of an undirected graph. We obtain significant speedups on XMT over the only published optimal (linear-time) serial implementation of a triconnected components algorithm running on a modern CPU. To our knowledge, no other parallel implementation of a triconnected components algorithm has been published for any platform. Burrows-Wheeler compression: We present novel work-optimal parallel algorithms for Burrows-Wheeler compression and decompression of strings over a constant alphabet and their empirical evaluation. To validate these theoretical algorithms, we implement them on XMT and show speedups of up to 25x for compression, and 13x for decompression, versus bzip2, the de facto standard implementation of Burrows-Wheeler compression. Fast Fourier transform (FFT): Using FFT as an example, we examine the impact that adoption of some enabling technologies, including silicon photonics, would have on the performance of a many-core architecture. The results show that a single-chip many-core processor could potentially outperform a large high-performance computing cluster. Boosted decision trees: This chapter focuses on the hybrid memory architecture of the XMT computer platform, a key part of which is a flexible all-to-all interconnection network that connects processors to shared memory modules. First, to understand some recent advances in GPU memory architecture and how they relate to this hybrid memory architecture, we use microbenchmarks including list ranking. Then, we contrast the scalability of applications with that of routines. In particular, regardless of the scalability needs of full applications, some routines may involve smaller problem sizes, and in particular smaller levels of parallelism, perhaps even serial. To see how a hybrid memory architecture can benefit such applications, we simulate a computer with such an architecture and demonstrate the potential for a speedup of 3.3X over NVIDIA's most powerful GPU to date for XGBoost, an implementation of boosted decision trees, a timely machine learning approach. Boolean satisfiability (SAT): SAT is an important performance-hungry problem with applications in many problem domains. However, most work on parallelizing SAT solvers has focused on coarse-grained, mostly embarrassing parallelism. Here, we study fine-grained parallelism that can speed up existing sequential SAT solvers. We show the potential for speedups of up to 382X across a variety of problem instances. We hope that these results will stimulate future research