Why Is Dual-Pivot Quicksort Fast?

I discuss the new dual-pivot Quicksort that is nowadays used to sort arrays of primitive types in Java. I sketch theoretical analyses of this algorithm that offer a possible, and in my opinion plausible, explanation why (a) dual-pivot Quicksort is faster than the previously used (classic) Quicksort and (b) why this improvement was not already found much earlier.Comment: extended abstract for Theorietage 2015 (https://www.uni-trier.de/index.php?id=55089) (v2 fixes a small bug in the pseudocode

Optimizing simulation on shared-memory platforms: The smart cities case

Modern advancements in computing architectures have been accompanied by new emergent paradigms to run Parallel Discrete Event Simulation models efficiently. Indeed, many new paradigms to effectively use the available underlying hardware have been proposed in the literature. Among these, the Share-Everything paradigm tackles massively-parallel shared-memory machines, in order to support speculative simulation by taking into account the limits and benefits related to this family of architectures. Previous results have shown how this paradigm outperforms traditional speculative strategies (such as data-separated Time Warp systems) whenever the granularity of executed events is small. In this paper, we show performance implications of this simulation-engine organization when the simulation models have a variable granularity. To this end, we have selected a traffic model, tailored for smart cities-oriented simulation. Our assessment illustrates the effects of the various tuning parameters related to the approach, opening to a higher understanding of this innovative paradigm

ORCHESTRA: an asyncrhonous non-blocking distributed GVT algorithm

Taking advantage of high computing capabilities of modern distributed architectures is fundamental to run large-scale simulation models based on the Parallel Discrete Event Simulation (PDES) paradigm. In particular, by exploiting clusters of modern multi-core architectures it is possible to efficiently overcome both the power and the memory wall. This is more the case when relying on the speculative Time Warp simulation protocol. Nevertheless, to ensure the correctness of the simulation, a form of coordination such as the GVT is fundamental. To increase the scalability of this mandatory synchronization, we present in this paper a coordination algorithm for clusters of share-everything multi-core simulation platoforms which is both wait-free and asynchronous. The nature of this protocol allows any computing node to carry on simulation activities while the global agreement is reached

An Agent-Based Simulation API for Speculative PDES Runtime Environments

Agent-Based Modeling and Simulation (ABMS) is an effective paradigm to model systems exhibiting complex interactions, also with the goal of studying the emergent behavior of these systems. While ABMS has been effectively used in many disciplines, many successful models are still run only sequentially. Relying on simple and easy-to-use languages such as NetLogo limits the possibility to benefit from more effective runtime paradigms, such as speculative Parallel Discrete Event Simulation (PDES). In this paper, we discuss a semantically-rich API allowing to implement Agent-Based Models in a simple and effective way. We also describe the critical points which should be taken into account to implement this API in a speculative PDES environment, to scale up simulations on distributed massively-parallel clusters. We present an experimental assessment showing how our proposal allows to implement complicated interactions with a reduced complexity, while delivering a non-negligible performance increase

PGAS Model for the Implementation of Scalable Cluster Systems

This paper introduces an extended version of the traditional Partitioned Global Address Space (PGAS) model, for the implementation of scalable cluster systems, that the HyperTransport Consortium Advanced Technology Group (ATG) is working on. Using the Simics and GEMS simulators, we developed a software module that approximates the behavior of a PGAS cluster. This approach mainly provides the simplest mechanism to evaluate how much the PGAS infrastructure will affect overall the application performance. The aim of this work is to study the feasibility of the ATG’s PGAS model for running applications with high memory requirements. Such a model, will let manufacturers build clusters that enable the execution of these applications, in such a way that it will be impossible to run them in a single processor, or in a multi–processor

Simulation Environment with Customized RISC-V Instructions for Logic-in-Memory Architectures

Nowadays, various memory-hungry applications like machine learning algorithms are knocking "the memory wall". Toward this, emerging memories featuring computational capacity are foreseen as a promising solution that performs data process inside the memory itself, so-called computation-in-memory, while eliminating the need for costly data movement. Recent research shows that utilizing the custom extension of RISC-V instruction set architecture to support computation-in-memory operations is effective. To evaluate the applicability of such methods further, this work enhances the standard GNU binary utilities to generate RISC-V executables with Logic-in-Memory (LiM) operations and develop a new gem5 simulation environment, which simulates the entire system (CPU, peripherals, etc.) in a cycle-accurate manner together with a user-defined LiM module integrated into the system. This work provides a modular testbed for the research community to evaluate potential LiM solutions and co-designs between hardware and software