Search Results for "cpu benchmark linux"
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Showing 10 open source projects for "cpu benchmark linux"
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miRPV
miRPV: An automated pipeline for miRNA Prediction and Validation in si
miRPV is an Automated tool that allows users to predict and validate microRNA from genome/gene sequence. System Requirement CPU: AMD64 (64bit) Memory: 2Gb RAM Storage: 5Gb Ubuntu 18.04 -
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slimfastq
An efficient lossless compression for fastq files.
slimfastq is a cli application that compresses/decompresses fastq files. It features: * High compression ratio * Relatively low cpu/memory usage * Truly lossless compression/decompression -
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This project, initially developed at University College London, contains programs to perform rigid, affine and non-linear registration of nifti or analyse images. Two versions of the algorithms are included, a CPU- and a GPU- (using CUDA) based implementation.
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fast_count_multi
Extremely fast NGS read counter
Counts NGS read alignments against GTF annotations in a multithreaded and scalable fashion. Benchmark: 8 core 1M annotations for 2Gb sorted reads ~30 seconds compared to ~28 minutes for bedtools multicov. Files include: fast_count_multi - reports all counts and RPKM, multithreading support fast_count_deseq - reports gene counts in deseq compatible format, multithreading support fast_count - reports all counts with no multithreading support. usage ./fast_count_multi... -
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MICA-aligner
Next-generation sequencing short reads aligner based on Intel® MIC
Latest Code in GitHub: https://github.com/aquaskyline/MICA-aligner To better utilize MIC-enabled computers for NGS data analysis, we developed a new short-read aligner MICA that is optimized in view of MIC’s limitation and the extra parallelism inside each MIC core. Experiments on aligning 150bp paired-end reads show that MICA using one MIC board is ~4.85 times faster than the CPU-(multi-core)-based BWA-MEM and about the same speed as the GPU-based SOAP3-dp. Furthermore, MICA’s... -
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SOAP3-DP
Fast, Accurate and Sensitive GPU-based Short Read Aligner
Latest Code on GitHub: https://github.com/aquaskyline/SOAP3-dp SOAP3-dp, through leveraging the computational power of both CPU and GPU with optimized algorithms, delivers high speed and sensitivity simultaneously. Compared with widely adopted aligners including BWA, Bowtie2, SeqAlto, CUSHAW2, GEM and GPU-based aligners BarraCUDA and CUSHAW, SOAP3-dp was found to be two to tens of times faster, while maintaining the highest sensitivity and lowest false discovery rate (FDR) on Illumina... -
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CUSHAW2: Parallel Gapped Read Alignment
One of the leading short-/long-read aligner to large genomes
CUSHAW2 is a fast and parallel gapped read alignment to large genomes, such as the human genome. The performance evaluation, by aligning simulated and real datasets to the human genome, shows that CUSHAW2 is consistently among the highest-ranked aligners in terms of alignment quality for both single-end and paired-end alignment, while demonstrating highly competitive speed. Furthermore, our aligner shows good parallel scalability with respect to the number of CPU threads. -
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PASHA: Parallelized Short Read Assembly
One of the fastest parallel short read assemblers for large genomes.
PASHA is a parallel short read assembler for large genomes using de Bruijn graphs. Taking advantage of both shared-memory multi-core CPUs and distributed-memory compute clusters, PASHA has demonstrated its potential to perform high-quality de-novo assembly of large genomes in reasonable time with modest computing resources. Our evaluation using three small real paired-end datasets shows that PASHA is able to produce better assemblies with comparable genome coverage and mis-assembly rates... -
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MUMmerGPU is a high-throughput DNA sequence alignment program that runs on nVidia G80-class GPUs. It aligns sequences in parallel on the video card to accelerate the widely used serial CPU program MUMmer.
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openevo is a project started to find out about behaviour of evolutionary generated machine code. It implements a certain set of CPU instruction codes and a few interrupts for interaction with the runtime environment.
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