Apache Arrow DataFusion is a fast, embeddable, and extensible query engine written in Rust that uses Apache Arrow as its memory model. In this paper we describe the technologies on which it is built, and how it fits in long-term database implementation ...

Regular Expressions (REs) matching is crucial to identify strings exhibiting certain morphological properties in a data stream, resulting paramount in contexts such as deep packet inspection in computer security and genome analysis in bioinformatics. Yet,...

Traditional blockchain systems still struggle with limited throughput, particularly those compatible with EVM, which are crucial in many blockchain applications. One of the main reasons arises from serial execution, which doesn’t exploit parallelism in ...

Block-STM is a parallel execution engine for smart contracts, built around the principles of Software Transactional Memory. Transactions are grouped in blocks, and every execution of the block must yield the same deterministic outcome. Block-STM further ...

Traditional public blockchain systems typically had very limited transaction throughput because of the bottleneck of the consensus protocol itself. With recent advances in consensus technology, the performance limit has been greatly lifted, typically to ...

Miners and validators in current blockchains serially execute block transactions. Such serial execution cannot efficiently utilize modern multi-core resources, consequently hampering system throughput. We propose three approaches to improve blockchain ...

Response Time Analysis (RTA) is an effective method for testing the schedulability of real-time tasks on multiprocessor platforms. Existing RTAs for global fixed priority scheduling calculate the upper bound of the worst case response time of each task. ...

Most of the data generated on high-performance computing systems are transferred to storage in remote systems for various purposes such as backup. To detect data corruption caused by network or storage failures during data transfer, the receiver system ...

New applications such as smart homes, smart cities, and autonomous vehicles are driving an increased interest in deploying machine learning on edge devices. Unfortunately, deploying deep neural networks (DNNs) on resource-constrained devices presents ...

To leverage the benefits of modern hardware, dynamic languages must support parallelism, and parallelism requires a virtual machine (VM) capable of parallel execution — a parallel VM. However, unrestricted concurrency and the dynamism of dynamic ...

A key problem in parallel programming is how data is partitioned: divided into subsets that can be operated on in parallel and, in distributed memory machines, spread across multiple address spaces.

We present a dependent partitioning framework that ...

Using agent-based simulation ABS to analyze complex adaptive systems gains growing popularity over the past decades. One of the fundamental issues in ABS is to increase the execution speed. In this paper, we identify two common modules that widely exist ...

In this paper we present an approach taken to run multiple Kepler sessions at the same time. This kind of execution is one of the requirements for Integrated Tokamak Modelling platform developed by the Nuclear Fusion community within the context of ...

In this work we present Armadillo a compilation chain used for compiling applications written in a high-level language (C++) to work on encrypted data. The back-end of the compilation chain is based on homomorphic encryption. The tool-chain further ...

Scientific workflows allow scientists to conduct experiments that manipulate data with multiple computational activities using Scientific Workflow Management Systems SWfMSs. As the scale of the data increases, SWfMSs need to support workflow execution ...

IaaS providers often allow the users to specify many requirements for their applications. However, users without advanced technical knowledge usually do not provide a good specification of the cloud environment, leading to low performance and/or high ...

Secure computation on private data has been an active area of research for many years and has received a renewed interest with the emergence of cloud computing. In recent years, substantial progress has been made with respect to the efficiency of the ...

Very large sparse matrices are often processed on massively parallel computer systems with distributed memory architectures consisting of tens or hundreds of thousands of processor cores. The problem occurs when we want or need to load/store these ...

Sparse matrix-vector multiplication (shortly spM V) is one of the most common subroutines in the numerical linear algebra. The parallelization of this task looks easy and straightforward, but it is not optimal in general case. This paper discuss some ...

OpenCL is an open standard for heterogeneous parallel programming, exploiting multi-core CPUs, GPUs, or other accelerators as parallel computing resources. Recent work has extended the OpenCL parallel programming model for distributed heterogeneous ...