Parallel Computing and Optimization Techniques

GeneF: A High-Performance Processing-in-Memory Accelerator for Efficient DNA Alignment

GeneF is a PIM accelerator for DNA alignment that achieves significant speedups and energy efficiency over CPU implementations.

MolAR: memory-safe library for analysis of MD simulations written in Rust

MolAR is a memory-safe Rust library for analyzing MD simulations, demonstrating high performance and offering memory-safe abstractions for molecular analysis software.

mm2-gb: GPU Accelerated Minimap2 for Long Read DNA Mapping

mm2-gb accelerates Minimap2's chaining step on GPU, improving performance for long DNA reads without sacrificing accuracy.

CUDASW++4.0: Ultra-fast GPU-based Smith-Waterman Protein Sequence Database Search

CUDASW++4.0 improves protein sequence database search speed using GPU-based Smith-Waterman alignment with performance gains over previous methods and CPU tools.

BIMSA: Accelerating Long Sequence Alignment Using Processing-In-Memory

BIMSA accelerates long sequence alignment using Processing-In-Memory, achieving significant speedups over existing PIM and CPU implementations.

Accelerated Dynamic Time Warping on GPU forSelective Nanopore Sequencing

DTWax optimizes the sDTW algorithm for GPU to improve sequencing speed and compute efficiency in nanopore sequencing.

A GPU-based computational framework that bridges Neuron simulation and Artificial Intelligence

This paper introduces a GPU-based framework that accelerates neuron simulations and applies it to neuroscience and AI tasks, showing significant speed improvements over traditional methods.

Efficient simulation of neural development using shared memory parallelization

NeuroDevSim simulates neural development using shared memory parallelization, achieving near-linear scaling up to 128 cores for medium to large models.

NeuroGPU, software for NEURON modeling in GPU-based hardware

NeuroGPU accelerates biophysically detailed neuronal simulations on GPUs, enabling faster parameter exploration and model fitting.

Integrating GPU support for FreeSurfer with OpenACC

This paper accelerates FreeSurfer using OpenACC, reducing programming costs and improving performance with GPU support.

CLIJ: GPU-accelerated image processing for everyone

CLIJ provides GPU-accelerated image processing through a Fiji plugin, enabling faster workflows on consumer hardware.

Scaling computational genomics to millions of individuals with GPUs

This paper demonstrates that GPU-accelerated machine learning libraries significantly speed up and reduce the cost of computational genomics tasks like QTL mapping and Bayesian non-negative matrix factorization.