• Corpus ID: 221136090

PANDA: Processing-in-MRAM Accelerated De Bruijn Graph based DNA Assembly

  title={PANDA: Processing-in-MRAM Accelerated De Bruijn Graph based DNA Assembly},
  author={Shaahin Angizi and Naima Ahmed Fahmi and W. Zhang and Deliang Fan},
Spurred by widening gap between data processing speed and data communication speed in Von-Neumann computing architectures, some bioinformatic applications have harnessed the computational power of Processing-in-Memory (PIM) platforms. However, the performance of PIMs unavoidably diminishes when dealing with such complex applications seeking bulk bit-wise comparison or addition operations. In this work, we present an efficient Processing-in-MRAM Accelerated De Bruijn Graph based DNA Assembly… 



PIM-Assembler: A Processing-in-Memory Platform for Genome Assembly

A high-throughput and energy-efficient Processing-in-DRAM-accelerated genome assembler called PIM-Assembler based on an optimized and hardware-friendly genome assembly algorithm that can assemble large-scale DNA sequence dataset from all-pair overlaps is proposed.

AlignS: A Processing-In-Memory Accelerator for DNA Short Read Alignment Leveraging SOT-MRAM

This paper presents a novel, customized, highly parallel read alignment algorithm that only seeks the proposed simple and parallel in-memory operations (i.e. comparisons and additions) and improves the short read alignment throughput per Watt per mm2 by ~12× compared to the ASIC accelerator.

Parallel De Bruijn Graph Construction and Traversal for De Novo Genome Assembly

A novel algorithm is provided that leverages one-sided communication capabilities of the Unified Parallel C (UPC) to facilitate the requisite fine-grained parallelism and avoidance of data hazards, while analytically proving its scalability properties.

PIM-Aligner: A Processing-in-MRAM Platform for Biological Sequence Alignment

A high-throughput and energy-efficient Processing-in-Memory accelerator (PIM-Aligner) to execute DNA short read alignment based on an optimized and hardware-friendly alignment algorithm that outperforms recent platforms based on dynamic programming.

GPU-Accelerated Bidirected De Bruijn Graph Construction for Genome Assembly

Preliminary results show that the GPU-accelerated graph construction on an NVIDIA S1070 server achieves a speedup of around two times over previous performance results on a 1024-node IBM Blue Gene/L.

An Efficient GPU-Based de Bruijn Graph Construction Algorithm for Micro-Assembly

A GPU-based de Bruijn graph construction algorithm for micro-assembly in the GATK HaplotypeCaller is proposed to improve its performance and shows a speedup of up to 2.66x.

A DNA Read Alignment Accelerator Based on Computational RAM

This article presents an in-memory accelerator architecture for DNA read alignment that outperforms corresponding software implementation by >49X and >18 000X, in terms of throughput and energy efficiency, respectively, even under conservative assumptions.

AligneR: A Process-in-Memory Architecture for Short Read Alignment in ReRAMs

AligneR, a ReRAM-based process-in-memory architecture, is proposed to accelerate the bottleneck of genome sequencing, i.e., short read alignment, and improves the short read aligned throughput per Watt.

Leveraging FPGAs for Accelerating Short Read Alignment

This architecture exploits the reconfigurability of FPGAs to allow the development of fast yet flexible alignment designs, and is implemented and evaluated on a 1U Maxeler MPC-X2000 dataflow node with eight Altera Stratix-V FPGA.

GPU-Euler: Sequence Assembly Using GPGPU

This work implemented an Eulerian-based sequence assembler (GPU-Euler) on the nVidia GPUs using the CUDA programming interface and demonstrated the promise of using GPUs for genome assembly, a computationally intensive task.