Search results for "vectorization"

Neighbor-list-free molecular dynamics on sunway TaihuLight supercomputer

2020

Molecular dynamics (MD) simulations are playing an increasingly important role in many research areas. Pair-wise potentials are widely used in MD simulations of bio-molecules, polymers, and nano-scale materials. Due to a low compute-to-memory-access ratio, their calculation is often bounded by memory transfer speeds. Sunway TaihuLight is one of the fastest supercomputers featuring a custom SW26010 many-core processor. Since the SW26010 has some critical limitations regarding main memory bandwidth and scratchpad memory size, it is considered as a good platform to investigate the optimization of pair-wise potentials especially in terms of data reusage. MD algorithms often use a neighbor-list …

Lipoproteins LDL versus HDL as nanocarriers to target either cancer cells or macrophages

2020

free open access article 31 p.; International audience; In this work, we have explored natural unmodified low- and high-density lipoproteins (LDL and HDL) as selective delivery vectors in colorectal cancer therapy. We show in vitro in cultured cells and in vivo (NanoSPECT/CT) in the CT-26 mice colorectal cancer model that LDLs are mainly taken up by cancer cells, while HDLs are preferentially taken up by macrophages. We loaded LDLs with cisplatin and HDLs with the heat shock protein-70 inhibitor AC1LINNC, turning them into a pair of “Trojan horses” delivering drugs selectively to their target cells as demonstrated in vitro in human colorectal cancer cells and macrophages, and in vivo. Coupl…

Vectors of Pairwise Item Preferences

2019

Neural embedding has been widely applied as an effective category of vectorization methods in real-world recommender systems. However, its exploration of users’ explicit feedback on items, to create good quality user and item vectors is still limited. Existing neural embedding methods only consider the items that are accessed by the users, but neglect the scenario when a user gives high or low rating to a particular item. In this paper, we propose Pref2Vec, a method to generate vector representations of pairwise item preferences, users and items, which can be directly utilized for machine learning tasks. Specifically, Pref2Vec considers users’ pairwise item preferences as elementary units. …

Pairwise DNA Sequence Alignment Optimization

2015

This chapter presents a parallel implementation of the Smith-Waterman algorithm to accelerate the pairwise alignment of DNA sequences. This algorithm is especially computationally demanding for long DNA sequences. Parallelization approaches are examined in order to deeply explore the inherent parallelism within Intel Xeon Phi coprocessors. This chapter looks at exploiting instruction-level parallelism within 512-bit single instruction multiple data instructions (vectorization) as well as thread-level parallelism over the many cores (multithreading using OpenMP). Between coprocessors, device-level parallelism through the compute power of clusters including Intel Xeon Phi coprocessors using M…

Fast MATLAB assembly of FEM matrices in 2D and 3D: Edge elements

2014

We propose an effective and flexible way to assemble finite element stiffness and mass matrices in MATLAB. We apply this for problems discretized by edge finite elements. Typical edge finite elements are Raviart-Thomas elements used in discretizations of H(div) spaces and Nedelec elements in discretizations of H(curl) spaces. We explain vectorization ideas and comment on a freely available MATLAB code which is fast and scalable with respect to time.

Hardware-efficient matrix inversion algorithm for complex adaptive systems

2012

This work shows an FPGA implementation for the matrix inversion algebra operation. Usually, large matrix dimension is required for real-time signal processing applications, especially in case of complex adaptive systems. A hardware efficient matrix inversion procedure is described using QR decomposition of the original matrix and modified Gram-Schmidt method. This works attempts a direct VHDL description using few predefined packages and fixed point arithmetic for better optimization. New proposals for intermediate calculations are described, leading to efficient logic occupation together with better performance and accuracy in the vector space algebra. Results show that, for a relatively s…

Carbon nanotube – Protamine hybrid: Evaluation of DNA cell penetration

2016

International audience; Carbon nanotubes (CNTs) represent a class of nanomaterials with important potential for biomedical and biotechnological applications. CNT based vectorization is an emerging approach to the transport of nucleic acid through cell membrane but limited by detachment of DNA and degradation process. To increase DNA internalization, it was proved that cationic functionalized CNT was essential. In such a way, protamine efficiently used in several transfection processes is a cationic protein which was never associated to CNT.We propose here a novel nanovector based on single-walled carbon nanotubes (SWCNT) functionalized by protamine. Our results based on qPCR methods clearly…

A potential solution to avoid overdose of mixed drugs in the event of Covid-19: Nanomedicine at the heart of the Covid-19 pandemic.

2021

Since 2020, the world is facing the first global pandemic of 21st century. Among all the solutions proposed to treat this new strain of coronavirus, named SARS-CoV-2, the vaccine seems a promising way but the delays are too long to be implemented quickly. In the emergency, a dual therapy has shown its effectiveness but has also provoked a set of debates around the dangerousness of a particular molecule, hydroxychloroquine. In particular, the doses to be delivered, according to the studies, were well beyond the acceptable doses to support the treatment without side effects. We propose here to use all the advantages of nanovectorization to address this question of concentration. Using quantum…

Automatic Conversion Technique from Data Dependent Triangulation to SVG B-Splines

2005

Optimization of Reactive Force Field Simulation: Refactor, Parallelization, and Vectorization for Interactions

2022

Molecular dynamics (MD) simulations are playing an increasingly important role in many areas ranging from chemical materials to biological molecules. With the continuing development of MD models, the potentials are getting larger and more complex. In this article, we focus on the reactive force field (ReaxFF) potential from LAMMPS to optimize the computation of interactions. We present our efforts on refactoring for neighbor list building, bond order computation, as well as valence angles and torsion angles computation. After redesigning these kernels, we develop a vectorized implementation for non-bonded interactions, which is nearly $100 \times$ 100 × faster than the management processing…