22 papers · ranked by Valyu relevance
Temitayo Adefemi
—Parallelization has become a cornerstone of modern computing, influencing everything from high-performance supercomputers to everyday mobile devices. This paper presents a comprehensive guide on the fundamentals of parallelization that every computer scientist should know, beginning with a historical perspective that…
Rajendra Purohit, K. R. Chowdhary, Sunıl Dutt Purohıt
—Arrival of multicore systems has enforced a new scenario in computing, the parallel and distributed algorithms are fast replacing the older sequential algorithms, with many challenges of these techniques. The distributed algorithms provide distributed processing using distributed file systems and processing units…
Laure Gonnord, Ludovic Henrio, Lionel Morel, Gabriel Radanne
Parallelism is often required for performance. In these situations an excess of non-determinism is harmful as it means the program can have several different behaviours or even different results. Even in domains such as high-performance computing where parallelism is crucial for performance, the computed value should…
Parinaz Barakhshan, Rudolf Eigenmann
We compare automatically and manually parallelized NAS Benchmarks in order to identify code sections that differ. We discuss opportunities for advancing automatic parallelizers. We find ten patterns that pose challenges for current parallelization technology. We also measure the potential impact of advanced techniques…
Brian Homerding, Atmn Patel, Enrico Armenio Deiana, Yian Su + 5 more
'Zujun Tan' 'Ziyang Xu' 'Bhargav Reddy Godala' 'David I. August' 'Simone Campanoni'] A compiler's intermediate representation (IR) defines a program's execution plan by encoding its instructions and their relative order. Compiler optimizations aim to replace a given execution plan (which instructions to execute and…
David S. Cerutti, Rafal Wiewiora, Simon Boothroyd, Woody Sherman
The Structure and TOpology Replica Molecular Mechanics (STORMM) code is a next-generation molecular simulation engine and associated libraries optimized for performance on fast, multicore central processor units (CPUs) and graphics processing units (GPUs) with independent memory and tens of thousands of threads. STORMM…
Denis Los, Igor Petushkov
Cores Authors: ['Denis Los' 'Igor Petushkov'] Abstract—Nowadays, latency-critical, high-performance applications are parallelized even on power-constrained client systems to improve performance. However, an important scenario of fine-grained tasking on simultaneous multithreading CPU cores in such systems has not been…
Agostino Dovier, Andrea Formisano, Gopal Gupta, Manuel V. Hermenegildo + 2 more
'Manuel V. Hermenegildo' 'Enrico Pontelli' 'Ricardo Rocha'] Multi-core and highly-connected architectures have become ubiquitous, and this has brought renewed interest in language-based approaches to the exploitation of parallelism. Since its inception, logic programming has been recognized as a programming paradigm…
Authors not listed
With the ever-increasing demand for atomistic structures representative of real-life systems as well as the ad-vent of exascale computers, it has now become necessary and possible to use advanced global optimization (GO) techniques to intelligently sample the potential energy surface (PES). Given the previous studies…
Patrick Mukala
| Article Info | ABSTRACT | | --- | --- | | | A myriad of applications ranging from engineering and scientific | | | simulations, image and signal processing as well as high-sensitive data | | | retrieval demand high processing power reaching up to teraflops for their | | | efficient execution. While a standard serial…
Tanveer Ahmad, Chengxin Ma, Zaid Al-Ars, H. Peter Hofstee
Current cluster scaled genomics data processing solutions rely on big data frameworks like Apache Spark, Hadoop and HDFS for data scheduling, processing and storage. These frameworks come with additional computation and memory overheads by default. It has been observed that scaling genomics dataset processing beyond 32…
Felix Kallenborn, Fawaz Dabbaghie, Martin Steinegger, Bertil Schmidt
The continually increasing volume of sequence data results in a growing demand for fast implementations of core algorithms. Computation of pairwise alignments based on dynamic programming is an important part in many bioinformatics pipelines and a major contributor to overall runtime due to the associated quadratic…
Authors not listed
This paper presents GLAS (Git-based Lab Automated Scheduler or Get Lab Automation Simplified), an open-source, robust, and highly expandable Git-based architecture designed for laboratory automation. GLAS can be deployed in both partially and fully automated experimental science laboratories, enabling the development…
Ghanshyam Chandra, Md. Vasimuddin, Sanchit Misra, Chirag Jain
Recent advancements in long-read sequencing and assembly methods have ushered in an era of high-quality genome assemblies. Modern assemblies commonly feature megabase-long sequences frequently spanning entire chromosomes. The increase in the assembly contiguity and the reduced number of assembly contigs also implies…
Peiyu Zong, Wenpeng Deng, Jian Liu, Jue Ruan
The rapid advancements in sequencing length necessitate the adoption of increasingly efficient sequence alignment algorithms. The Needleman-Wunsch method introduces the foundational dynamic programming (DP) matrix calculation for global alignment, which evaluates the overall alignment of sequences. However, this method…
Bertil Schmidt, Felix Kallenborn, Alejandro Chacon, Christian Hundt
The maximal sensitivity for local pairwise alignment makes the Smith-Waterman algorithm a popular choice for protein sequence database search. However, its quadratic time complexity makes it compute-intensive. Unfortunately, current state-of-the-art software tools are not able to leverage the massively parallel…
Haojing Shao, Jue Ruan
Increasing the accuracy of the nucleotide sequence alignment is an essential issue in genomics research. Although classic dynamic-programming algorithms (e.g., Smith-Waterman and Needleman–Wunsch) guarantee to produce the optimal result, their time complexity hinders the application of large-scale sequence alignment.…
Authors not listed
Protein conformational landscapes contain the functionally relevant information useful for understanding biological processes. Mapping out conformational landscapes provides valuable insights into protein behaviors and biological phenomena, and has relevance to therapeutic design. While experimental structural biology…
Alexander S. Shved, Blake E. Ocampo, Elena S. Burlova, Casey L. Olen + 2 more
The construction, management and analysis of large in silico molecular libraries is critical in many areas of modern chemistry. Herein, we introduce the MOLecular LIibrary toolkit, "molli", which is a Python 3 cheminformatics module that provides a streamlined interface for manipulating large in silico libraries.…
Authors not listed
The python package ArchOnML ("Archive-On-Machine-Learning") is introduced, which can perform virtual screening projects covering up to millions of structural derivatives through the use of Kernel Ridge Regression models. It supports the full workflow of setting up calculation inputs for external quantum chemistry…
Authors not listed
Background: Pharmaceutical batch scheduling in multi-reactor configurations presents complex optimization challenges under operational uncertainty, yet limited research addresses how parallel processing capacity affects heuristic performance and predictive modeling. Objectives: This study investigated scheduling…
Peter Kraus, Edan Bainglass, Francisco F. Ramirez, Enea Svaluto-Ferro + 7 more
Compliance with good research data management practices means trust in the integrity of the data, and it is achievable by a full control of the data gathering process. In this work, we demonstrate tooling which bridges these two aspects, and illustrate its use in a case study of automated battery cycling. We…