Ramasse-miettes générationnel et incémental gérant les cycles et les gros objets en utilisant des frames délimités

Ces dernières années, des recherches ont été menées sur plusieurs techniques reliées à la collection des déchets. Plusieurs découvertes centrales pour le ramassage de miettes par copie ont été réalisées. Cependant, des améliorations sont encore possibles. Dans ce mémoire, nous introduisons des nouvelles techniques et de nouveaux algorithmes pour améliorer le ramassage de miettes. En particulier, nous introduisons une technique utilisant des cadres délimités pour marquer et retracer les pointeurs racines. Cette technique permet un calcul efficace de l'ensemble des racines. Elle réutilise des concepts de deux techniques existantes, card marking et remembered sets, et utilise une configuration bidirectionelle des objets pour améliorer ces concepts en stabilisant le surplus de mémoire utilisée et en réduisant la charge de travail lors du parcours des pointeurs. Nous présentons aussi un algorithme pour marquer récursivement les objets rejoignables sans utiliser de pile (éliminant le gaspillage de mémoire habituel). Nous adaptons cet algorithme pour implémenter un ramasse-miettes copiant en profondeur et améliorer la localité du heap. Nous améliorons l'algorithme de collection des miettes older-first et sa version générationnelle en ajoutant une phase de marquage garantissant la collection de toutes les miettes, incluant les structures cycliques réparties sur plusieurs fenêtres. Finalement, nous introduisons une technique pour gérer les gros objets. Pour tester nos idées, nous avons conçu et implémenté, dans la machine virtuelle libre Java SableVM, un cadre de développement portable et extensible pour la collection des miettes. Dans ce cadre, nous avons implémenté des algorithmes de collection semi-space, older-first et generational. Nos expérimentations montrent que la technique du cadre délimité procure des performances compétitives pour plusieurs benchmarks. Elles montrent aussi que, pour la plupart des benchmarks, notre algorithme de parcours en profondeur améliore la localité et augmente ainsi la performance. Nos mesures de la performance générale montrent que, utilisant nos techniques, un ramasse-miettes peut délivrer une performance compétitive et surpasser celle des ramasses-miettes existants pour plusieurs benchmarks. ______________________________________________________________________________ MOTS-CLÉS DE L’AUTEUR : Ramasse-Miettes, Machine Virtuelle, Java, SableVM

Statistiline lähenemine mälulekete tuvastamiseks Java rakendustes

Kaasaegsed hallatud käitusaja keskkonnad (ingl. managed runtime environment) ja programmeerimiskeeled lihtsustavad rakenduste loomist ning haldamist. Kõige levinumaks näiteks säärase keele ja keskkonna kohta on Java. Üheks tähtsaks hallatud käitusaja keskkonna ülesandeks on automaatne mäluhaldus. Vaatamata sisseehitatud prügikoristajale, mälulekke probleem Javas on endiselt relevantne ning tähendab tarbetut mälu hoidmist. Probleem on eriti kriitiline rakendustes mis peaksid ööpäevaringselt tõrgeteta toimima, kuna mäluleke on üks väheseid programmeerimisvigu mis võib hävitada kogu Java rakenduse. Parimaks indikaatoriks otsustamaks kas objekt on kasutuses või mitte on objekti viimane kasutusaeg. Selle meetrika põhiliseks puudujäägiks on selle hind jõudluse mõttes. Käesolev väitekiri uurib mälulekete problemaatikat Javas ning pakub välja uudse mälulekkeid tuvastava ning diagnoosiva algoritmi. Väitekirjas kirjeldatakse alternatiivset lähenemisviisi objektide kasutuse hindamiseks. Põhihüpoteesiks on idee et lekkivaid objekte saab statistiliste meetoditega eristada mittelekkivatest kui vaadelda objektide populatsiooni eluiga erinevate gruppide lõikes. Pakutud lähenemine on oluliselt odavama hinnaga jõudluse mõttes, kuna objekti kohta on vaja salvestada infot ainult selle loomise hetkel. Väitekirja uurimistöö tulemusi on rakendatud mälulekete tuvastamise tööriista Plumbr arendamisel, mida hetkel edukalt kasutatakse ka erinevates toodangkeskkondades. Pärast sissejuhatavaid peatükke, väitekirjas vaadeldakse siiani pakutud lahendusi ning on pakutud välja ka nende meetodite klassifikatsioon. Järgnevalt on kirjeldatud statistiline baasmeetod mälulekete tuvastamiseks. Lisaks on analüüsitud ka kirjeldatud baasmeetodi puudujääke. Järgnevalt on kirjeldatud kuidas said defineeritud lisamõõdikud mis aitasid masinõppe abil baasmeetodit täpsemaks teha. Testandmeid masinõppe tarbeks on kogutud Plumbri abil päris rakendustest ning toodangkeskkondadest. Lisaks, kirjeldatakse väitekirjas juhtumianalüüse ning võrdlust ühe olemasoleva mälulekete tuvastamise lahendusega.Modern managed runtime environments and programming languages greatly simplify creation and maintenance of applications. One of the best examples of such managed runtime environments and a language is the Java Virtual Machine and the Java programming language. Despite the built in garbage collector, the memory leak problem is still relevant in Java and means wasting memory by preventing unused objects from being removed. The problem of memory leaks is especially critical for applications, which are expected to work uninterrupted around the clock, as running out of memory is one of a few reasons which may cause the termination of the whole Java application. The best indicator of whether an object is used or not is the time of the last access. However, the main disadvantage of this metric is the incurred performance overhead. Current thesis researches the memory leak problem and proposes a novel approach for memory leak detection and diagnosis. The thesis proposes an alternative approach for estimation of the 'unusedness' of objects. The main hypothesis is that leaked objects may be identified by applying statistical methods to analyze lifetimes of objects, by observing the ages of the population of objects grouped by their allocation points. Proposed solution is much more efficient performance-wise as for each object it is sufficient to record any information at the time of creation of the object. The research conducted for the thesis is utilized in a memory leak detection tool Plumbr. After the introduction and overview of the state of the art, current thesis reviews existing solutions and proposes the classification for memory leak detection approaches. Next, the statistical approach for memory leak detection is described along with the description of the main metric used to distinguish leaking objects from non-leaking ones. Follows the analysis of this single metric. Based on this analysis additional metrics are designed and machine learning algorithms are applied on the statistical data acquired from real production environments from the Plumbr tool. Case studies of real applications and one previous solution for the memory leak detection are performed in order to evaluate performance overhead of the tool

PAEAN : portable and scalable runtime support for parallel Haskell dialects

Over time, several competing approaches to parallel Haskell programming have emerged. Different approaches support parallelism at various different scales, ranging from small multicores to massively parallel high-performance computing systems. They also provide varying degrees of control, ranging from completely implicit approaches to ones providing full programmer control. Most current designs assume a shared memory model at the programmer, implementation and hardware levels. This is, however, becoming increasingly divorced from the reality at the hardware level. It also imposes significant unwanted runtime overheads in the form of garbage collection synchronisation etc. What is needed is an easy way to abstract over the implementation and hardware levels, while presenting a simple parallelism model to the programmer. The PArallEl shAred Nothing runtime system design aims to provide a portable and high-level shared-nothing implementation platform for parallel Haskell dialects. It abstracts over major issues such as work distribution and data serialisation, consolidating existing, successful designs into a single framework. It also provides an optional virtual shared-memory programming abstraction for (possibly) shared-nothing parallel machines, such as modern multicore/manycore architectures or cluster/cloud computing systems. It builds on, unifies and extends, existing well-developed support for shared-memory parallelism that is provided by the widely used GHC Haskell compiler. This paper summarises the state-of-the-art in shared-nothing parallel Haskell implementations, introduces the PArallEl shAred Nothing abstractions, shows how they can be used to implement three distinct parallel Haskell dialects, and demonstrates that good scalability can be obtained on recent parallel machines.PostprintPeer reviewe

An efficient implementation of lazy functional programming languages based on the generalized intensional transformation

Αυτή η εργασία διερευνά θεωρητικά και πρακτικά ζητήματα της αλληλεπίδρασης μεταξύ (ευρέως γνωστών και νέων) τεχνικών μεταγλώττισης, όπως ο γενικευμένος νοηματικός μετασχηματισμός, ο μετασχηματισμός σε συναρτησιακά αντικείμενα, η ξεχωριστή μεταγλώττιση και η λάμβδα άρση. Ένας πειραματικός μεταγλωττιστής για τη γλώσσα Haskell (GIC), ο οποίος χρησιμοποιεί τις τεχνικές αυτές, δίνει τη δυνατότητα σε νέες ιδέες να υλοποιηθούν και να αξιολογηθούν μέσα σε ένα πρακτικό πλαίσιο. Ως μέρος αυτής της δουλειάς πραγματοποιήθηκαν διάφορες προσθήκες και αλλαγές στο μεταγλωττιστή, είτε προκειμένου να γίνει ο μεταγλωττιστής πληρέστερος είτε προκειμένου να βελτιωθεί ο τελικός κώδικας που παράγεται από το LAR back-end του μεταγλωττιστή.This dissertation investigates theoretical and practical issues of the integration between (well-known and novel) compilation techniques, such as the generalized intensional transformation, defunctionalization, separate compilation, and lambda lifting. An experimental Haskell compiler (GIC), which incorporates these techniques, serves as a workbench allowing ideas to be demonstrated and evaluated in a practical context. Within the scope of this work, several additions and changes were made to the compiler either towards enchancing the tool’s robustness or towards the optimization of the code generated by the compiler’s LAR back-end

Precise garbage collection for C

Journal ArticleMagpie is a source-to-source transformation for C programs that enables precise garbage collection, where precise means that integers are not confused with pointers, and the liveness of a pointer is apparent at the source level. Precise GC is primarily useful for long-running programs and programs that interact with untrusted components. In particular, we have successfully deployed precise GC in the C implementation of a language run-time system that was originally designed to use conservative GC. We also report on our experience in transforming parts of the Linux kernel to use precise GC instead of manual memory management

Simple, safe, and efficient memory management using linear pointers

Efficient and safe memory management is a hard problem. Garbage collection promises automatic memory management but comes with the cost of increased memory footprint, reduced parallelism in multi-threaded programs, unpredictable pause time, and intricate tuning parameters balancing the program's workload and designated memory usage in order for an application to perform reasonably well. Existing research mitigates the above problems to some extent, but programmer error could still cause memory leak by erroneously keeping memory references when they are no longer needed. We need a methodology for programmers to become resource aware, so that efficient, scalable, predictable and high performance programs may be written without the fear of resource leak. Linear logic has been recognized as the formalism of choice for resource tracking. It requires explicit introduction and elimination of resources and guarantees that a resource cannot be implicitly shared or abandoned, hence must be linear. Early languages based on linear logic focused on Curry-Howard correspondence. They began by limiting the expressive powers of the language and then reintroduced them by allowing controlled sharing which is necessary for recursive functions. However, only by deviating from Curry-Howard correspondence could later development actually address programming errors in resource usage. The contribution of this dissertation is a simple, safe, and efficient approach introducing linear resource ownership semantics into C++ (which is still a widely used language after 30 years since inception) through linear pointer, a smart pointer inspired by linear logic. By implementing various linear data structures and a parallel, multi-threaded memory allocator based on these data structures, this work shows that linear pointer is practical and efficient in the real world, and that it is possible to build a memory management stack that is entirely leak free. The dissertation offers some closing remarks on the difficulties a formal system would encounter when reasoning about a concurrent linear data algorithm, and what might be done to solve these problems

The design and construction of high performance garbage collectors

Garbage collection is a performance-critical component of modern language implementations. The performance of a garbage collector depends in part on major algorithmic decisions, but also significantly on implementation details and techniques which are often incidental in the literature. In this dissertation I look in detail at the performance characteristics of garbage collection on modern architectures. My thesis is that a thorough understanding of the characteristics of the heap to be collected, coupled with measured performance of various design alternatives on a range of modern architectures provides insights that can be used to improve the performance of any garbage collection algorithm. The key contributions of this work are: 1) A new analysis technique (replay collection) for measuring the performance of garbage collection algorithms; 2) a novel technique for applying software prefetch to non-moving garbage collectors that achieves significant performance gains; and 3) a comprehensive analysis of object scanning techniques, cataloguing and comparing the performance of the known methods, and leading to a new technique that optimizes performance without significant cost to the runtime environment. These contributions are applicable to a wide range of garbage collectors, and can provide significant measurable speedups to a design point where each implementer in the past has had to trust intuition or their own benchmarking. The methodologies and implementation techniques contributed in this dissertation have the potential to make a significant improvement to the performance of every garbage collector

Garbage Collection for General Graphs

Garbage collection is moving from being a utility to a requirement of every modern programming language. With multi-core and distributed systems, most programs written recently are heavily multi-threaded and distributed. Distributed and multi-threaded programs are called concurrent programs. Manual memory management is cumbersome and difficult in concurrent programs. Concurrent programming is characterized by multiple independent processes/threads, communication between processes/threads, and uncertainty in the order of concurrent operations. The uncertainty in the order of operations makes manual memory management of concurrent programs difficult. A popular alternative to garbage collection in concurrent programs is to use smart pointers. Smart pointers can collect all garbage only if developer identifies cycles being created in the reference graph. Smart pointer usage does not guarantee protection from memory leaks unless cycle can be detected as process/thread create them. General garbage collectors, on the other hand, can avoid memory leaks, dangling pointers, and double deletion problems in any programming environment without help from the programmer. Concurrent programming is used in shared memory and distributed memory systems. State of the art shared memory systems use a single concurrent garbage collector thread that processes the reference graph. Distributed memory systems have very few complete garbage collection algorithms and those that exist use global barriers, are centralized and do not scale well. This thesis focuses on designing garbage collection algorithms for shared memory and distributed memory systems that satisfy the following properties: concurrent, parallel, scalable, localized (decentralized), low pause time, high promptness, no global synchronization, safe, complete, and operates in linear time