Accelerating a cross-correlation score function to search modifications using a single GPU
نویسندگان
چکیده
منابع مشابه
Accelerating Depth Image-Based Rendering Using GPU
In this paper, we propose a practical method for hardwareaccelerated rendering of the depth image-based representation (DIBR) object, which is defined in MPEG-4 Animation Framework eXtension (AFX). The proposed method overcomes the drawbacks of the conventional rendering, i.e. it is slow since it is hardly assisted by graphics hardware and surface lighting is static. Utilizing the new features ...
متن کاملAccelerating the XGBoost algorithm using GPU computing
We present a CUDA-based implementation of a decision tree construction algorithm within the gradient boosting library XGBoost. The tree construction algorithm is executed entirely on the graphics processing unit (GPU) and shows high performance with a variety of datasets and settings, including sparse input matrices. Individual boosting iterations are parallelised, combining two approaches. An ...
متن کاملGPU-Vote: A Framework for Accelerating Voting Algorithms on GPU
Voting algorithms, such as histogram and Hough transforms, are frequently used algorithms in various domains, such as statistics and image processing. Algorithms in these domains may be accelerated using GPUs. Implementing voting algorithms efficiently on a GPU however is far from trivial due to irregularities and unpredictable memory accesses. Existing GPU implementations therefore target only...
متن کاملComputing exact p-values for a cross-correlation shotgun proteomics score function.
The core of every protein mass spectrometry analysis pipeline is a function that assesses the quality of a match between an observed spectrum and a candidate peptide. We describe a procedure for computing exact p-values for the oldest and still widely used score function, SEQUEST XCorr. The procedure uses dynamic programming to enumerate efficiently the full distribution of scores for all possi...
متن کاملCUDAMPF++: A Proactive Resource Exhaustion Scheme for Accelerating Homologous Sequence Search on CUDA-enabled GPU
Genomic sequence alignment is an important research topic in bioinformatics and continues to attract significant efforts. As genomic data grow exponentially, however, most of alignment methods face challenges due to their huge computational costs. HMMER, a suite of bioinformatics tools, is widely used for the analysis of homologous protein and nucleotide sequences with high sensitivity, based o...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: BMC Bioinformatics
سال: 2018
ISSN: 1471-2105
DOI: 10.1186/s12859-018-2559-6