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Computer systems rely heavily on abstraction to manage the exponential growth of complexity across hardware and software. Due to practical considerations of compatibility between components of these complex systems across generations, developers have favou ...

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 ...

Data races have long been a notorious problem in concurrent programming. They are subtle to detect, and lead to non-deterministic behaviours. There has been a lot of interest in type systems that statically guarantee data race freedom. Significant progress ...

Agent-based simulations have been widely applied in many disciplines, by scientists and engineers alike. Scientists use agent-based simulations to tackle global problems, including alleviating poverty, reducing violence, and predicting the impact of pandem ...

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 ...

Dataflow programming is a methodology that enables the development of high-level, parametric programs that are independent of the underlying platform. This approach is particularly useful for heterogeneous platforms, as it eliminates the need to rewrite ap ...

Advances in computational capabilities and large volumes of experimental data have established computer simulations of brain tissue models as an important pillar in modern neuroscience. Alongside, a variety of domain specific languages (DSLs) have been dev ...

Virtual Memory (VM) is a critical programming abstraction that is widely used in various modern computing platforms. With the rise of datacenter computing and birth of planet-scale online services, the semantic and capacity requirements from memory have ev ...

Type-level programming is becoming more and more popular in the realm of functional programming. However, the combination of type-level programming and subtyping remains largely unexplored in practical programming languages. This paper presents match types ...

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 ...

Formal verification of real-world software systems remains challenging for a number of reasons, including lack of automation, friction in specifying properties, and limited support for the diverse programming paradigms used in industry. In this thesis we m ...

Recent GPU architectures make available numbers of parallel processing units that exceed by orders of magnitude the ones offered by CPU architectures. Whereas programs written using dataflow programming languages are well suited for programming heterogeneo ...

Writing and optimizing application software for heterogeneous platforms including GPU units is a very difficult task that requires designer efforts and resources to consider several key elements to obtain good performance. Dataflow programming has shown to ...

The ability of dataflow circuits to implement dynamic scheduling promises to overcome the conservatism of static scheduling techniques that high-level synthesis tools typically rely on. Yet, the same distributed control mechanism that allows dataflow circu ...

Programming languages and systems have failed to address the security implications of the increasingly frequent use of public libraries to construct modern software. Most languages provide tools and online repositories to publish, import, and use libraries ...

Programming has changed; programming languages have not. Modern software embraced reusable software components, i.e., public libraries, and runs in the cloud, on machines that co-locate applications from various origins. This new programming paradigm leads ...

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 ...

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 ...

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 ...

Actors that Unify Threads and Events

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Secure Interface Design Leveraging Hardware/Software Support

Oligolithic Cross-task Optimizations across Isolated Workloads

Degrees of Separation: A Flexible Type System for Safe Concurrency

Generalizing Bulk-Synchronous Parallel Processing for Data Science: From Data to Threads and Agent-Based Simulations

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

Design Space Exploration for Partitioning Dataflow Program on CPU-GPU Heterogeneous System

MOD2IR: High-Performance Code Generation for a Biophysically Detailed Neuronal Simulation DSL

Rebooting Virtual Memory with Midgard

Type-Level Programming with Match Types

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

Scaling Language Features for Program Verification

Inter-actions parallel execution on GPU from high-level dataflow synthesis

SIMD Parallel Execution on GPU from High-Level Dataflow Synthesis

A Comprehensive Timing Model for Accurate Frequency Tuning in Dataflow Circuits

Enclosure: Language-Based Restriction of Untrusted Libraries

Trust as a Programming Primitive

High-Level Synthesis of Dynamically Scheduled Circuits

Just-in-time performance without warm-up

Safe initialization of objects

Task scheduling for highly concurrent analytical and transaction workloads