FPGA Accelerated Bioinformatics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook FPGA Accelerated Bioinformatics write by Nathaniel McVicar. This book was released on 2018. FPGA Accelerated Bioinformatics available in PDF, EPUB and Kindle. Advances in next-generation sequencing technology have led to increases in genomic data production by sequencing machines that outpace Moore’s law. This trend has reached the point where the time and money spent processing human and other genome sequence data could be greater than that spent producing it. Field-Programmable Gate Arrays (FPGAs) can provide a solution to this problem. Bioinformatics accelerators running on FPGAs achieve order of magnitude speedups across a variety of genomics applications important in both biological research and clinical medicine. This dissertation presents three accelerators. The first addresses the short read alignment problem, where millions of short DNA or RNA reads, with lengths on the order of 100 base pairs, are aligned to an index built from a reference genome. Our aligner combines an FPGA accelerator with the greater memory bandwidth of our host system to produce a fast and flexible short read aligner. Using this aligner, we developed a classifier to determine which of two possible species each read originated from. In a case study with RNA-Seq reads from mouse and human retinal cultures our aligner produced more accurate classification results and better performance than software-based aligners. Our second accelerator tackles the problem of non-coding RNA (ncRNA) homology search. The biologically important functions these ncRNAs perform are determined by their two- or three-dimensional structure, and ncRNAs with different sequences can perform the same functions if they share a similar structure. Homology search scores sequences using models of ncRNA families in an effort to find previously unknown members. Our accelerator greatly improves the speed of filters that identify candidate sequences using the Viterbi and CYK algorithms. The final accelerator uses the Hybrid Memory Cube (HMC), a stacked DRAM, for K-mer counting. In many areas of bioinformatics, including de novo assembly, K-mer counting is a filter with important roles including removing read errors. Our approach stores K-mer counts in a Bloom filter on the HMC leveraging the greater random access rate for increased performance over both the host and FPGA-attached DRAM. Throughout this dissertation we demonstrate that FPGA accelerators can achieve excellent speedups across a variety of genomics applications.
Architecture Exploration of FPGA Based Accelerators for BioInformatics Applications
Architecture Exploration of FPGA Based Accelerators for BioInformatics Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Architecture Exploration of FPGA Based Accelerators for BioInformatics Applications write by B. Sharat Chandra Varma. This book was released on 2016-03-02. Architecture Exploration of FPGA Based Accelerators for BioInformatics Applications available in PDF, EPUB and Kindle. This book presents an evaluation methodology to design future FPGA fabrics incorporating hard embedded blocks (HEBs) to accelerate applications. This methodology will be useful for selection of blocks to be embedded into the fabric and for evaluating the performance gain that can be achieved by such an embedding. The authors illustrate the use of their methodology by studying the impact of HEBs on two important bioinformatics applications: protein docking and genome assembly. The book also explains how the respective HEBs are designed and how hardware implementation of the application is done using these HEBs. It shows that significant speedups can be achieved over pure software implementations by using such FPGA-based accelerators. The methodology presented in this book may also be used for designing HEBs for accelerating software implementations in other domains besides bioinformatics. This book will prove useful to students, researchers, and practicing engineers alike.
Accelerated Systems for Portable DNA Sequencing
Accelerated Systems for Portable DNA Sequencing - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Accelerated Systems for Portable DNA Sequencing write by Harisankar Sadasivan. This book was released on 2023-04-30. Accelerated Systems for Portable DNA Sequencing available in PDF, EPUB and Kindle. The MinION is a revolutionary handheld DNA sequencer that is inexpensive, portable, and can perform real-time sequencing. MinION is increasingly used in Precision Medicine applications. However, the MinION lacks portable compute power. This thesis introduces two clinical applications of the MinION and identifies and solves performance bottlenecks through hardware and software solutions to enable portable microbial diagnostics. Finally, we discuss how our accelerated solutions will fit on a laptop with a GPU. More than 99% of DNA fragments in a typical human sample are non-target (human), which may be skipped in real-time using the MinION’s Read Until feature. We analyze the performance of the Read Until pipeline in detecting target microbial species for targeted viral pathogen detection and microbiome abundance estimation. We find new sources of performance bottlenecks (basecaller in the classification of a fragment) that are not addressed by past genomics accelerators. While SquiggleFilter and DTWax are our solutions for targeted viral pathogen detection, RawMap is for untargeted microbiome analysis. We also discuss accelerating the bottleneck step in the DNA mapping software (Minimap2) used in all of MinION’s sequencing workflows. For targeted virus detection, we discuss SquiggleFilter which is a portable and programmable hardware-software solution that directly analyzes MinION’s raw squiggles and filters everything except target viral DNA fragments. SquiggleFilter avoids the expensive basecalling step and uses hardware accelerated subsequence Dynamic Time Warping (sDTW). We show that our 14.3W 13.25 sq. mm accelerator has 274× greater throughput and 3481× lower latency than existing GPU-based solutions while consuming half the power. DTWax overcomes the on-chip memory limitations of SquiggleFilter by optimizing its high-accuracy sDTW algorithm for GPUs resulting in a ∼1.92X sequencing speedup and ∼3.64X compute speedup: costup. For the untargeted classification and analysis of microbiome, we discuss RawMap which is a machine-learning-based smart and efficient solution that reduces sequencing time and cost by ∼24% and computing cost by ∼22%. We also discuss how RawMap may be used as an alternative to the RT-PCR test for viral load quantification of SARS-CoV-2. Minimap2 is a software used in all MinION workflows. minimap2-accelerated (mm2-ax) is a heterogeneous design for sequence mapping where minimap2’s bottleneck step is sped up on the GPU with bit-exact output. mm2-ax on an NVIDIA A100 GPU improves the bottleneck step (chaining) with 4.07 - 1.93X speedup: costup over a SIMD baseline. Finally, we envision a portable solution to microbial diagnostics with a laptop connected to the MinION. DTWax can perform targeted virus detection on the GPU and RawMap does untargeted microbiome classification on the CPU. Post-sequencing tasks like basecalling, alignment (using mm2-ax) and variant calling use the GPU.
High-Performance Computing Using FPGAs
High-Performance Computing Using FPGAs - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook High-Performance Computing Using FPGAs write by Wim Vanderbauwhede. This book was released on 2013-08-23. High-Performance Computing Using FPGAs available in PDF, EPUB and Kindle. High-Performance Computing using FPGA covers the area of high performance reconfigurable computing (HPRC). This book provides an overview of architectures, tools and applications for High-Performance Reconfigurable Computing (HPRC). FPGAs offer very high I/O bandwidth and fine-grained, custom and flexible parallelism and with the ever-increasing computational needs coupled with the frequency/power wall, the increasing maturity and capabilities of FPGAs, and the advent of multicore processors which has caused the acceptance of parallel computational models. The Part on architectures will introduce different FPGA-based HPC platforms: attached co-processor HPRC architectures such as the CHREC’s Novo-G and EPCC’s Maxwell systems; tightly coupled HRPC architectures, e.g. the Convey hybrid-core computer; reconfigurably networked HPRC architectures, e.g. the QPACE system, and standalone HPRC architectures such as EPFL’s CONFETTI system. The Part on Tools will focus on high-level programming approaches for HPRC, with chapters on C-to-Gate tools (such as Impulse-C, AutoESL, Handel-C, MORA-C++); Graphical tools (MATLAB-Simulink, NI LabVIEW); Domain-specific languages, languages for heterogeneous computing(for example OpenCL, Microsoft’s Kiwi and Alchemy projects). The part on Applications will present case from several application domains where HPRC has been used successfully, such as Bioinformatics and Computational Biology; Financial Computing; Stencil computations; Information retrieval; Lattice QCD; Astrophysics simulations; Weather and climate modeling.
Bioinformatics: FPGA-based accelerators for bioinformatics applications
Bioinformatics: FPGA-based accelerators for bioinformatics applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Bioinformatics: FPGA-based accelerators for bioinformatics applications write by . This book was released on 2013. Bioinformatics: FPGA-based accelerators for bioinformatics applications available in PDF, EPUB and Kindle.
