High-Performance Transactional Event Processing

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Enterprises collect data in large volumes and leverage them to drive numerous concurrent decisions and business processes. Their teams deploy multiple applications that often operate concurrently on the same data and infrastructure but have widely differen ...

Most modern in-memory online transaction processing (OLTP) engines rely on multi-version concurrency control (MVCC) to provide data consistency guarantees in the presence of conflicting data accesses. MVCC improves concurrency by generating a new version o ...

Today's continued increase in demand for processing power, despite the slowdown of Moore's law, has led to an increase in processor count, which has resulted in energy consumption and distribution problems. To address this, there is a growing trend toward ...

Analytical workloads are evolving as the number of users surges and applications that submit queries in batches become popular. However, traditional analytical databases that optimize-then-execute each query individually struggle to provide timely response ...

The hardware complexity of modern machines makes the design of adequate programming models crucial for jointly ensuring performance, portability, and productivity in high-performance computing (HPC). Sequential task-based programming models paired with adv ...

The performance of programs executed on heterogeneous parallel platforms largely depends on the design choices regarding how to partition the processing on the various different processing units. In other words, it depends on the assumptions and parameters ...

Transaction processing is a central part of most database applications. While serializability remains the gold standard for desirable transactional semantics, many database systems offer improved transaction throughput at the expense of introducing potenti ...

Utilization of edge devices has exploded in the last decade, with such use cases as wearable devices, autonomous driving, and smart homes. As their ubiquity grows, so do expectations of their capabilities. Simultaneously, their formfactor and use cases lim ...

High-Level Synthesis (HLS) tools generate hardware designs from high-level programming languages. These tools almost universally build datapaths that are controlled using a centralized controller which relies on a static, compile-time schedule to determine ...

Scala has been developed as a language that deeply integrates with the Java ecosystem. It offers seamless interoperability with existing Java libraries. Since the Scala compiler targets Java bytecode, Scala programs have access to high-performance runtimes ...

Systems and method for a task scheduler with dynamic adjustment of concurrency levels and task granularity are disclosed for improved execution of highly concurrent analytical and transactional systems. The task scheduler can avoid both over commitment and ...

In this thesis, we revisit classic problems in shared-memory distributed computing through the lenses of (1) emerging hardware technologies and (2) changing requirements. Our contributions consist, on the one hand, in providing a better understanding of th ...

The inception of object-oriented programming introduces a category of bugs related to object construction: initialization errors. Every newly created object goes through several initialization states: starting from a state where all fields are uninitialize ...

Modern large-scale data platforms manage colossal amount of data, generated by the ever-increasing number of concurrent users. Geo-replicated and sharded key-value data stores play a central role when building such platforms. As the strongest consistency m ...

Database systems access memory either sequentially or randomly. Contrary to sequential access and despite the extensive efforts of computer architects, compiler writers, and system builders, random access to data larger than the processor cache has been s ...

Transactions can simplify distributed applications by hiding data distribution, concurrency, and failures from the application developer. Ideally the developer would see the abstraction of a single large machine that runs transactions sequentially and neve ...

Current online applications, such as search engines, social networks, or file sharing services, execute across a distributed network of machines. They provide non-stop services to their users despite failures in the underlying network. To achieve such a hi ...

Geo-replicated data platforms are the backbone of several large-scale online services. Transactional Causal Consistency (TCC) is an attractive consistency level for building such platforms. TCC avoids many anomalies of eventual consistency, eschews the syn ...

Simulations of the electrical activity of networks of morphologically-detailed neuron models allow for a better understanding of the brain. Short time to solution is critical in order to study long biological processes such as synaptic plasticity and learn ...

As hardware evolves, so do the needs of applications. To increase the performance of an application, there exist two well-known approaches. These are scaling up an application, using a larger multi-core platform, or scaling out, by distributing work to mul ...

High-Performance Transactional Event Processing

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Oligolithic Cross-task Optimizations across Isolated Workloads

One-shot Garbage Collection for In-memory OLTP through Temporality-aware Version Storage

Compilation and Design Space Exploration of Dataflow Programs for Heterogeneous CPU-GPU Platforms

Efficient Concurrent Analytical Query Processing using Data and Workload-conscious Sharing

Decentralized in-order execution of a sequential task-based code for shared-memory architectures

Performance Estimation of High-Level Dataflow Program on Heterogeneous Platforms by Dynamic Network Execution

Robustness Against Read Committed: A Free Transactional Lunch

In-Memory Hardware and Architectural Extensions for Workloads Acceleration

High-Level Synthesis of Dynamically Scheduled Circuits

Just-in-time performance without warm-up

Task scheduling for highly concurrent analytical and transaction workloads

Distributed Computing with Modern Shared Memory

Safe initialization of objects

Efficient Protocols for Enforcing Causal Consistency in Geo-Replicated Key-Value Data Stores

Improving Main-memory Database System Performance through Cooperative Multitasking

Fast General Distributed Transactions with Opacity

System Support for Efficient Replication in Distributed Systems

PaRiS: Causally Consistent Transactions with Non-blocking Reads and Partial Replication

Asynchronous Simulation of Neuronal Activity

Scalable Synchronization in Shared-Memory Systems: Extrapolating, Adapting, Tuning