libcppa - Designing an Actor Semantic for C++11

Parallel hardware makes concurrency mandatory for efficient program execution. However, writing concurrent software is both challenging and error-prone. C++11 provides standard facilities for multiprogramming, such as atomic operations with acquire/release semantics and RAII mutex locking, but these primitives remain too low-level. Using them both correctly and efficiently still requires expert knowledge and hand-crafting. The actor model replaces implicit communication by sharing with an explicit message passing mechanism. It applies to concurrency as well as distribution, and a lightweight actor model implementation that schedules all actors in a properly pre-dimensioned thread pool can outperform equivalent thread-based applications. However, the actor model did not enter the domain of native programming languages yet besides vendor-specific island solutions. With the open source library libcppa, we want to combine the ability to build reliable and distributed systems provided by the actor model with the performance and resource-efficiency of C++11.Comment: 10 page

CloudTPS: Scalable Transactions for Web Applications in the Cloud

NoSQL Cloud data services provide scalability and high availability properties for web applications but at the same time they sacrifice data consistency. However, many applications cannot afford any data inconsistency. CloudTPS is a scalable transaction manager to allow cloud database services to execute the ACID transactions of web applications, even in the presence of server failures and network partitions. We implement this approach on top of the two main families of scalable data layers: Bigtable and SimpleDB. Performance evaluation on top of HBase (an open-source version of Bigtable) in our local cluster and Amazon SimpleDB in the Amazon cloud shows that our system scales linearly at least up to 40 nodes in our local cluster and 80 nodes in the Amazon cloud

COMBINE: An Improved Directory-Based Consistency Protocol

This paper presents COMBINE, a directory-based consistency protocol for shared objects, designed for large-scale distributed systems with unreliable links. Directory-based consistency protocols support move requests, allowing to write the object locally, as well as lookup requests, providing a read-only copy of the object. They have been used in distributed shared memory implementations and are a key element of data-flow implementations of distributed software transactional memory in large-scale systems. The protocol runs on an overlay tree, whose leaves are the nodes of the system, and its main novelty is in combining requests that overtake each other as they pass through the same node. Combining requests on a simple tree structure allows the protocol to tolerate non-fifo links and handle concurrent requests. Combining also avoids race conditions and ensures that the cost of serving a request is proportional to the cost of the shortest path between the requesting node and the serving node, in the overlay tree. Using an overlay tree with a good stretch factor yields an efficient protocol

TM2C: A software transactional memory for many-cores

Transactional memory is an appealing paradigm for concurrent programming. Many software implementations of the paradigm were proposed in the last decades for both shared memory multi-core systems and clusters of distributed machines. However, chip manufacturers have started producing many-core architectures, with low network-on-chip communication latency and limited support for cache-coherence, rendering existing transactional memory implementations inapplicable. This paper presents TM2C, the first software Transactional Memory protocol for Many-Core systems. TM2C exploits network-on-chip communications to get granted accesses to shared data through efficient message passing. In particular, it allows visible read accesses and hence effective distributed contention management with eager conflict detection. We also propose FairCM, a companion contention manager that ensures starvation-freedom, which we believe is an important property in many-core systems, as well as an implementation of elastic transactions in these settings. Our evaluation on four benchmarks, i.e., a linked list and a hash table data structures as well as a bank and a MapReduce-like applications, indicates better scalability than locks and up to 20-fold speedup (relative to bare sequential code) when running 24 application cores. © 2012 ACM

Mesobi: memória transacional em software tolerante a faltas bizantinas

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Ciência da Computação, Florianópolis, 2015.Memória Transacional em Software (STM) é um modelo utilizado para tratar acesso concorrente a dados compartilhados, onde programadores não precisam lidar explicitamente com mecanismos de controle de concorrência, como locks. O programador, apenas delineia qual parte do código necessita ser tratado como concorrente e sua execução seguirá o modelo transacional, respeitando as propriedades: atomicidade, consistência e isolação. É proposto nessa dissertação um modelo denominado Mesobi: Memória Transacional em Software Tolerante a Faltas Bizantinas onde transações somente leitura não abortam. Existem algumas abordagens na literatura que utilizam Memória Transacional em Software, das quais grande parte tolera faltas de parada mas pouco se fala sobre faltas maliciosas. Somente o trabalho de Zhang 2012 faz tolerância a faltas Bizantinas no contexto de STM; sua proposta utiliza dois clusters para alcançar tolerância a faltas Bizantinas.No modelo de Zhang, transações somente leitura podem ser abortadas, não é suportada a execução de transações interativas e não é possível executar transações de forma otimista. O Mesobi permite alcançar tolerância a faltas Bizantinas utilizando (3f+1) réplicas, sendo que, f é o número de faltas toleradas. O modelo consiste em inicialmente tentar executar as transações de forma otimista sem a necessidade de executar o protocolo Bizantino. Transações conflitantes localmente não são iniciadas de imediato com isso evita-se trabalho improdutivo. É possível e viável a execução de transações pré-declaradas e interativas no mesmo ambiente, sendo que, transações interativas têm pior desempenho devido a sua maior troca de mensagens.Abstract : Software Transactional Memory (STM) is a model to deal concurrent accesses on shared data. With STM developers do not need to cope with explicit concurrency control mechanisms like locks. Instead developers can write parallel portions of code as transactions, which are garanteed to execute atomically and in isolation regardless of eventual data races. In this dissertation we propose a model named Mesobi: Memória Transacional em Software Tolerante a Faltas Bizantinas in which read-only transactions do not abort. There are some approaches in literature that use STM, but most of them treat crash faults, but few deal with arbitrary faults. The work presented by Zhang 2012 mentions Byzantine Fault Tolerance (BFT) in STM context, but two clusters are necessary, one for consensus and another to execute transactions. Zhang's model abort read-only transactions, does not use optimistic execution neither interactive transactions processing. It achieves BFT using (3f+1) replicas where f represents the number of tolerated faults. The model executes in an optimistic fashion the transactions without the BFT protocol. Conflicting local transactions are not executed immediately thereby saving wasted work. Execution and consistency tests showed that execution of interactive and pre-declared transactions on same environment are possible and practical. Interactive transactions have worse performance than pre-declared due to need of more message exchanges

Scheduling in Transactional Memory Systems: Models, Algorithms, and Evaluations

Transactional memory provides an alternative synchronization mechanism that removes many limitations of traditional lock-based synchronization so that concurrent program writing is easier than lock-based code in modern multicore architectures. The fundamental module in a transactional memory system is the transaction which represents a sequence of read and write operations that are performed atomically to a set of shared resources; transactions may conflict if they access the same shared resources. A transaction scheduling algorithm is used to handle these transaction conflicts and schedule appropriately the transactions. In this dissertation, we study transaction scheduling problem in several systems that differ through the variation of the intra-core communication cost in accessing shared resources. Symmetric communication costs imply tightly-coupled systems, asymmetric communication costs imply large-scale distributed systems, and partially asymmetric communication costs imply non-uniform memory access systems. We made several theoretical contributions providing tight, near-tight, and/or impossibility results on three different performance evaluation metrics: execution time, communication cost, and load, for any transaction scheduling algorithm. We then complement these theoretical results by experimental evaluations, whenever possible, showing their benefits in practical scenarios. To the best of our knowledge, the contributions of this dissertation are either the first of their kind or significant improvements over the best previously known results

Software Transactional Memory for Large Scale Clusters

While there has been extensive work on the design of software transactional memory (STM) for cache coherent shared memory systems, there has been no work on the design of an STM system for very large scale platforms containing potentially thousands of nodes. In this work, we present Cluster-STM, an STM designed for high performance on large-scale commodity clusters. Our design addresses several novel issues posed by this domain, including aggregating communication, managing locality, and distributing transactional metadata onto the nodes. We also re-evaluate several STM design choices previously studied for cache-coherent machines and conclude that, in some cases, different choices are appropriate on clusters. Finally, we show that our design scales well up to 512 processors. This is because on a cluster, the main barrier to STM scalability is the remote communication overhead imposed by the STM operations, and our design aggregates most of that communication with the communication of the underlying data