NECSTFridayTalk - Surfing the Wavefront of Genome Alignment
NECSTFridayTalk
Giulia Gerometta
Computer Science and Engineering Master Student
Politecnico di Milano
Event will be online from Facebook
April 29th, 2022
1.00 pm
Contacts:
Marco Santambrogio
Research Line:
System architectures
Giulia Gerometta
Computer Science and Engineering Master Student
Politecnico di Milano
Event will be online from Facebook
April 29th, 2022
1.00 pm
Contacts:
Marco Santambrogio
Research Line:
System architectures
Sommario
On April 29th, 2022 at 1.00 pm "Surfing the Wavefront of Genome Alignment" a new appointment of NECSTFridayTalk, will be held online via Facebook by Giulia Gerometta, Master student in Computer Science and Engineering at Politecnico di Milano.
Pairwise sequence alignment represents a fundamental step in genome and molecular analysis applications, accounting for most of their runtime. Given the quadratic time complexity of alignment algorithms, the community presses for the development of more efficient algorithms. Moreover, current limitations of general-purpose architectures push users to use hardware accelerators to reduce the analysis time. In this context, we present an FPGA implementation of the Wavefront Alignment (WFA) algorithm, a recently introduced solution that exploits homologous regions between the sequences to speed up the alignment process and whose complexity is related to the score of the alignment, rather than to the lengths of the sequences.
Our multicore design can achieve up to 8.09x improvement in speedup and 57.77x in energy efficiency compared to the multi-threaded software implementation run on a Xeon Gold Processor.
Moreover, our design highly outperforms the current State-of-the-Art hardware-accelerated solution, reaching up to 2876 Giga Cell Updates Per Second (GCUPS) and 68.47 GCUPS/W on a single FPGA, with an improvement of up to 2.29 x and 9.90x in terms of performance and energy efficiency, respectively.
Pairwise sequence alignment represents a fundamental step in genome and molecular analysis applications, accounting for most of their runtime. Given the quadratic time complexity of alignment algorithms, the community presses for the development of more efficient algorithms. Moreover, current limitations of general-purpose architectures push users to use hardware accelerators to reduce the analysis time. In this context, we present an FPGA implementation of the Wavefront Alignment (WFA) algorithm, a recently introduced solution that exploits homologous regions between the sequences to speed up the alignment process and whose complexity is related to the score of the alignment, rather than to the lengths of the sequences.
Our multicore design can achieve up to 8.09x improvement in speedup and 57.77x in energy efficiency compared to the multi-threaded software implementation run on a Xeon Gold Processor.
Moreover, our design highly outperforms the current State-of-the-Art hardware-accelerated solution, reaching up to 2876 Giga Cell Updates Per Second (GCUPS) and 68.47 GCUPS/W on a single FPGA, with an improvement of up to 2.29 x and 9.90x in terms of performance and energy efficiency, respectively.
The NECSTLab is a DEIB laboratory, with different research lines on advanced topics in computing systems: from architectural characteristics, to hardware-software codesign methodologies, to security and dependability issues of complex system architectures.
Every week, the “NECSTFridayTalk” invites researchers, professionals or entrepreneurs to share their work experiences and projects they are implementing in the “Computing Systems”.
Streaming will be available via Facebook