The spring semester 2021 will take place online until further notice. Exceptions: Courses that can only be carried out with on-site presence. Please note the information provided by the lecturers.

Mohammed H. K. Alser: Catalogue data in Spring Semester 2021

Name Dr. Mohammed H. K. Alser
Address
Dep. Inf.techno.u.Elektrotechnik
ETH Zürich, ETZ H 61.1
Gloriastrasse 35
8092 Zürich
SWITZERLAND
E-mailmohammed.alser@safari.ethz.ch
DepartmentInformation Technology and Electrical Engineering
RelationshipLecturer

NumberTitleECTSHoursLecturers
227-0085-33LProjects & Seminars: Accelerating Genome Analysis with FPGAs, GPUs, and New Execution Paradigms Restricted registration - show details
Only for Electrical Engineering and Information Technology BSc.

The course unit can only be taken once. Repeated enrollment in a later semester is not creditable.
3 credits3PM. H. K. Alser, J. Gómez Luna
AbstractThe category of "Laboratory Courses, Projects, Seminars" includes courses and laboratories in various formats designed to impart practical knowledge and skills. Moreover, these classes encourage independent experimentation and design, allow for explorative learning and teach the methodology of project work.
ObjectiveA genome encodes a set of instructions for performing some functions within our cells. Analyzing our genomes helps, for example, to determine differences in these instructions (known as genetic variations) from human to human that may cause diseases or different traits. One benefit of knowing the genetic variations is better understanding and diagnosis of diseases and the development of efficient drugs.

Computers are widely used to perform genome analysis using dedicated algorithms and data structures. However, timely analysis of genomic data remains a daunting challenge, due to the complex algorithms and large datasets used for the analysis. Increasing the number of processing cores used for genome analysis decreases the overall analysis time, but significantly escalates the cost of building, maintaining, and cooling such a computing cluster, as well as the power/energy consumed by the cluster. This is a critical shortcoming with respect to both energy production and environmental friendliness. Cloud computing platforms can be used as an alternative to distribute the workload, but transferring the data between the clinic and the cloud poses new privacy and legal concerns.

In this course, we will cover the basics of genome analysis to understand the computational steps of the entire pipeline and find the computational bottlenecks. Students will learn about the existing efforts for accelerating one or more of these steps and will have the chance to carry out a hands-on project to improve these efforts.

Prerequisites of the course:
- No prior knowledge in bioinformatics or genome analysis is required.
- Digital Design and Computer Architecture (or equivalent course)
- A good knowledge in C programming language is required.
- Experience in at least one of the following is highly desirable:
FPGA implementation and GPU programming.
- Interest in making things efficient and solving problems

The course is conducted in English.

Course website: https://safari.ethz.ch/projects_and_seminars/doku.php?id=bioinformatics

Learning Materials
===============
1. A survey on accelerating genome analysis: https://arxiv.org/pdf/2008.00961
2. A detailed survey on the state-of-the-art algorithms for sequencing data: https://arxiv.org/pdf/2003.00110
3. An example of how to accelerate genomic sequence matching by two orders of magnitude with the help of FPGAs or GPUs: https://arxiv.org/abs/1910.09020
4. An example of how to accelerate read mapping step by an order of magnitude and without using hardware acceleration: https://arxiv.org/pdf/1912.08735
5. An example of using a different computing paradigm for accelerating read mapping step and improving its energy consumption: https://arxiv.org/pdf/1708.04329
6. Two examples on using software/hardware co-design to accelerate genomic sequence matching by two orders of magnitude: https://arxiv.org/abs/1604.01789 https://arxiv.org/abs/1809.07858
227-0085-36LProjects & Seminars: Genome Sequencing on Mobile Devices Restricted registration - show details
Only for Electrical Engineering and Information Technology BSc.

The course unit can only be taken once. Repeated enrollment in a later semester is not creditable.
3 credits3PM. H. K. Alser, J. Gómez Luna
AbstractThe category of "Laboratory Courses, Projects, Seminars" includes courses and laboratories in various formats designed to impart practical knowledge and skills. Moreover, these classes encourage independent experimentation and design, allow for explorative learning and teach the methodology of project work.
ObjectiveGenome analysis is the foundation of many scientific and medical discoveries, and serves as a key enabler of personalized medicine. This analysis is currently limited by the inability of existing technologies to read an organism’s complete genome. Instead, a dedicated machine (called sequencer) extracts a large number of shorter random fragments of an organism’s DNA sequence, known as reads. Small, handheld sequencers such as ONT MinION and Flongle make it possible to sequence bacterial and viral genomes in the field, thus facilitating disease outbreak analyses such as COVID-19, Ebola, and Zika. However, large, capable computers are still needed to perform genome assembly, which tries to reassemble read fragments back into an entire genome sequence. This limits the benefits of mobile sequencing and may pose problems in rapid diagnosis of infectious diseases, tracking outbreaks, and near-patient testing. The problem is exacerbated in developing countries and during crises where access to the internet network, cloud services, or data centers is even more limited.

In this course, we will cover the basics of genome analysis to understand the speed-accuracy tradeoff in using computationally-lightweight heuristics versus accurate computationally-expensive algorithms. Such heuristic algorithms typically operate on a smaller dataset that can fit in the memory of today’s mobile device. Students will experimentally evaluate different heuristic algorithms and observe their effect on the end results. This evaluation will give the students the chance to carry out a hands-on project to implement one or more of these heuristic algorithms in their smartphones and help the society by enabling on-site analysis of genomic data.

Prerequisites of the course:
- No prior knowledge in bioinformatics or genome analysis is required.
- A good knowledge in C programming language and programming is required.
- Interest in making things efficient and solving problems

The course is conducted in English.

Course website: https://safari.ethz.ch/projects_and_seminars/doku.php?id=genome_seq_mobile

Learning Materials
===============
1. A survey on accelerating genome analysis: https://arxiv.org/pdf/2008.00961

2. A detailed survey on the state-of-the-art algorithms for sequencing data: https://arxiv.org/pdf/2003.00110

3. An example of how to accelerate genomic sequence matching by two orders of magnitude with the help of FPGAs or GPUs: https://arxiv.org/abs/1910.09020

4. An example of how to accelerate read mapping step by an order of magnitude and without using hardware acceleration: https://arxiv.org/pdf/1912.08735

5. An example of using a different computing paradigm for accelerating read mapping step and improving its energy consumption: https://arxiv.org/pdf/1708.04329

6. Two examples on using software/hardware co-design to accelerate genomic sequence matching by two orders of magnitude: https://arxiv.org/abs/1604.01789 https://arxiv.org/abs/1809.07858

7. An example of a purely software method for fast genome sequence analysis: http://www.biomedcentral.com/content/pdf/1471-2164-14-S1-S13.pdf
227-2211-00LSeminar in Computer Architecture Information Restricted registration - show details
Number of participants limited to 22.

The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar.
2 credits2SO. Mutlu, M. H. K. Alser, J. Gómez Luna
AbstractThis seminar course covers fundamental and cutting-edge research papers in computer architecture. It has multiple components that are aimed at improving students' (1) technical skills in computer architecture, (2) critical thinking and analysis abilities on computer architecture concepts, as well as (3) technical presentation of concepts and papers in both spoken and written forms.
ObjectiveThe main objective is to learn how to rigorously analyze and present papers and ideas on computer architecture. We will have rigorous presentation and discussion of selected papers during lectures and a written report delivered by each student at the end of the semester.

This course is for those interested in computer architecture. Registered students are expected to attend every meeting, participate in the discussion, and create a synthesis report at the end of the course.
ContentTopics will center around computer architecture. We will, for example, discuss papers on hardware security; accelerators for key applications like machine learning, graph processing and bioinformatics; memory systems; interconnects; processing in memory; various fundamental and emerging paradigms in computer architecture; hardware/software co-design and cooperation; fault tolerance; energy efficiency; heterogeneous and parallel systems; new execution models; predictable computing, etc.
Lecture notesAll materials will be posted on the course website: https://safari.ethz.ch/architecture_seminar/
Past course materials, including the synthesis report assignment, can be found in the Fall 2020 website for the course: https://safari.ethz.ch/architecture_seminar/fall2020/doku.php
LiteratureKey papers and articles, on both fundamentals and cutting-edge topics in computer architecture will be provided and discussed. These will be posted on the course website.
Prerequisites / NoticeDesign of Digital Circuits.
Students should (1) have done very well in Design of Digital Circuits and (2) show a genuine interest in Computer Architecture.