|
|
Think Big, Aim High, and Have a Wonderful 2021!
|
|
|
|
|
|
|
Happy New Year! We are excited to share our group highlights with you in this second edition of the SAFARI newsletter (You can find the first edition from April 2020 here). 2020 has brought many challenges and changes to all of our lives. We have adapted our scientific research and teaching to an online global presence. We continue to test and find creative ways to continue collaborations in our research and improve our online education. Thanks to the efforts of many people who have organized various events, we have had the pleasure of contributing to many virtual global conferences and meetings, spanning topics in computer architecture, computing systems, circuits and devices, bioinformatics, security, reliability, machine learning, reconfigurable computing, and more. We have continued to enjoy having fruitful interactions with our collaborators around the globe. We have also been honored and humbled to receive multiple prestigious awards, like the Best Paper Award at MICRO 2020 and IEEE Security and Privacy 2020 conferences, as well as the Pwnie Award for Most Innovative Research.
|
|
|
|
|
Our new building, ETZ, Gloriastrasse 35
|
|
Our group moved to the Department of Information Technology and Electrical Engineering (aka Electrical and Computer Engineering, D-ITET) in early October, where we have more space and a brand-new hardware research lab. We are very positive about this change and look forward to developing new and diverse collaborations across the computing stack, all the way from algorithms to devices, with our colleagues in our new department.
|
|
|
|
We have also expanded our educational activities at the bachelor and master's levels, adding new hands-on project courses in memory systems, processing in memory and genome analysis. We will continue to be affiliated with the Department of Computer Science, extending our collaborations and continuing to teach our freshman-level Digital Design and Computer Architecture class.
In this second edition of the SAFARI newsletter, we share our research, teaching and outreach highlights from 2020, and look ahead to a new and inspiring future in 2021.
|
We wish you a wonderful 2021, in all aspects of your lives!
|
|
|
|
|
Fun SAFARI fact: Have you ever wondered what SAFARI actually means? You are not alone. Many people have asked us, and we would like to share the meaning of SAFARI with you. SAFARI is the name first given to the research group Onur Mutlu started at Carnegie Mellon University in 2009. It originally stood for the research vision of the group at the time: SAfe, FAir, Robust and Intelligent computer architectures! The vision still forms a part of the research we do, but the group's focus has expanded over the years. Onur likes to think about the group's research as a SAFARI for new ideas and breakthroughs in computer architecture and bioinformatics.
|
|
|
News & Awards
|
|
|
|
|
BEER wins the Best Paper Award at MICRO 2020
|
Congratulations to Minesh Patel, Jeremie Kim, Taha Shahroodi, Hasan Hassan, and Onur Mutlu for the Best Paper Award at this year's IEEE/ACM International Symposium on Microarchitecture for their paper:
|
|
|
|
|
Onur received the IEEE Computer Society prestigious 2020 Edward J. McCluskey Technical Achievement Award for "innovative and impactful contributions to computer memory systems.” In honour of this achievement, the IEEE Computer Society have produced a commemorative video.
|
|
|
|
Jisung Park was awarded a Postdoctoral Research Fellowship from the National Research Foundation of Korea for his project on "Storage System Design for Machine Learning Applications". The NRF award "Fostering the Next Generation of Researchers" supports postdocs to maintain research continuity and foster their independent research capacity. Congratulations Jisung!
|
|
|
|
|
|
Nomination for the Stamatis Vassiliadis Memorial Best Paper Award at FPL 2020!
|
Congratulations to Gagandeep Singh and co-authors on their nomination for the Stamatis Vassiliadis Memorial Award at FPL2020!
|
|
|
|
Mohammad Sadrosadati, an affiliated postdoc with SAFARI, was awarded the Khwarizmi Youth Award. The award is a national version of the Khwarizmi International Award, open to Iranians under 35 years old "to honor young scientists and embolden them to keep taking even bigger steps in their research career". Congratulations Mohammad! Read more
|
|
|
|
|
|
|
|
|
|
|
Congratulations to Nastaran Hajinazar for the Best Picture Award at ISCA 2020!
|
|
|
|
|
Damla Senol Cali, Gurpreet S. Kalsi, Zulal Bingol, Can Firtina, Lavanya Subramanian, Jeremie S. Kim, Rachata Ausavarungnirun, Mohammed Alser, Juan Gomez-Luna, Amirali Boroumand, Anant Nori, Allison Scibisz, Sreenivas Subramoney, Can Alkan, Saugata Ghose, and Onur Mutlu
|
|
Minesh Patel, Jeremie S. Kim, Taha Shahroodi, Hasan Hassan, and Onur Mutlu
|
|
|
|
Yaohua Wang, Lois Orosa, Xiangjun Peng, Yang Guo, Saugata Ghose, Minesh Patel, Jeremie S. Kim, Juan Gómez Luna, Mohammad Sadrosadati, Nika Mansouri Ghiasi, and Onur Mutlu
|
|
Jawad Haj-Yahya, Mohammed Alser, Jeremie S. Kim, Lois Orosa, Efraim Rotem, Avi Mendelson, Anupam Chattopadhyay, and Onur Mutlu
|
|
|
|
|
We thank our industry partners for their continued and new support in 2020!
|
Our group was generously supported with new donations this year from Google, Huawei, Intel, SRC and VMware. We thank all of our industry partners for their continued support of our research, and our partners who have generously supported us with new donations this year. We also wish to thank the ETH Foundation for facilitating and supporting our industry relations and gift funding.
|
|
|
|
|
We always welcome generous donations and gifts to support our research. Please contact Onur for more information on donating and being a part of SAFARI supporters.
|
|
|
Selected Recent Publications
|
|
|
|
|
|
IEEE MICRO, Volume: 40, Issue: 05, Pages: 65-75, September/October 2020.
|
|
|
|
|
|
|
Minesh Patel, Jeremie S. Kim, Taha Shahroodi, Hasan Hassan, and Onur Mutlu
|
|
|
|
|
Damla Senol Cali, Gurpreet S. Kalsi, Zulal Bingol, Can Firtina, Lavanya Subramanian, Jeremie S. Kim, Rachata Ausavarungnirun, Mohammed Alser, Juan Gomez-Luna, Amirali Boroumand, Anant Nori, Allison Scibisz, Sreenivas Subramoney, Can Alkan, Saugata Ghose, and Onur Mutlu
|
|
|
|
|
|
|
Yaohua Wang, Lois Orosa, Xiangjun Peng, Yang Guo, Saugata Ghose, Minesh Patel, Jeremie S. Kim, Juan Gómez Luna, Mohammad Sadrosadati, Nika Mansouri Ghiasi, and Onur Mutlu
Proceedings of the 53rd International Symposium on Microarchitecture (MICRO). Virtual, October 2020.
|
|
|
|
|
|
|
|
Haocong Luo, Taha Shahroodi, Hasan Hassan, Minesh Patel, A. Giray Yaglikci, Lois Orosa, Jisung Park, and Onur Mutlu,
Proceedings of the 47th International Symposium on Computer Architecture (ISCA), Valencia, Spain, June 2020.
|
|
|
|
|
|
|
|
Nastaran Hajinazar, Pratyush Patel, Minesh Patel, Konstantinos Kanellopoulos, Saugata Ghose, Rachata Ausavarungnirun, Geraldo Francisco de Oliveira Jr., Jonathan Appavoo, Vivek Seshadri, and Onur Mutlu
|
|
|
|
|
Jawad Haj-Yahya, Mohammed Alser, Jeremie Kim, A. Giray Yaglikci, Nandita Vijaykumar, Efraim Rotem, and Onur Mutlu,
Proceedings of the 47th International Symposium on Computer Architecture (ISCA), Valencia, Spain, June 2020.
|
|
|
|
|
|
|
Mohammad Sadrosadati, Amirhossein Mirhosseini, Seyed Borna Ehsani, Hamid Sarbazi-Azad, Mario Drumond, Babak Falsafi, Rachata Ausavarungnirun, and Onur Mutlu
ACM Transactions on Computer Systems (TOCS), to appear in 2021. Paper PDF
|
|
|
|
|
|
|
Pietro Frigo, Emanuele Vannacci, Hasan Hassan, Victor van der Veen, Onur Mutlu, Cristiano Giuffrida, Herbert Bos, and Kaveh Razavi
Proceedings of the 41st IEEE Symposium on Security and Privacy (S&P), San Francisco, CA, USA, May 2020. Best paper award Pwnie Award 2020 for Most Innovative Research
|
|
|
|
|
|
Behzad Salami, Erhan Baturay Onural, Ismail Emir Yuksel, Fahrettin Koc, Oguz Ergin, Adrian Cristal Kestelman, Osman S. Unsal, Hamid Sarbazi-Azad, and Onur Mutlu
Proceedings of the 50th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), Valencia, Spain, June 2020.
|
|
|
|
|
|
|
Lucian Cojocar, Jeremie Kim, Minesh Patel, Lillian Tsai, Stefan Saroiu, Alec Wolman, Onur Mutlu
|
|
|
|
|
|
|
Jorge Gonzalez, Alexander Gazman, Maarten Hattink, Mauricio G. Palma, Meisam Bahadori, Ruth Rubio-Noriega, Lois Orosa, Madeleine Glick, Onur Mutlu, Keren Bergman, and Rodolfo Azevedo
Proceedings of the 32nd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD), Porto, Portugal, September 2020. Paper Slides (pptx) (pdf) Talk Video
|
|
|
|
|
|
|
Can Firtina, Jeremie S. Kim, Mohammed Alser, Damla Senol Cali, A. Ercument Cicek, Can Alkan, Onur Mutlu
|
|
|
|
|
|
Seyyed Hossein SeyyedAghaei Rezaei, Mehdi Modarressi, Rachata Ausavarungnirun, Mohammad Sadrosadati, Onur Mutlu, and Masoud Daneshtalab
IEEE Computer Architecture Letters (CAL): 2020, Volume: 19, Issue: 01, Pages: 80-83
|
|
|
|
|
Muhammad Shafique, Mahum Naseer, Theocharis Theocharides, Christos Kyrkou, Onur Mutlu, Lois Orosa, and Jungwook Choi
|
|
|
|
|
|
|
Feng Zhang, Jidong Zhai, Xipeng Shen, Dalin Wang, Zheng Chen, Onur Mutlu, Wenguang Chen, and Xiaoyong Du
VLDB Journal, September 2020.
|
|
|
|
|
|
|
Jiantong Jiang, Zeke Wang, Xue Liu, Juan Gómez-Luna, Nan Guan, Qingxu Deng, Wei Zhang, and Onur Mutlu
Proceedings of the 28th International Symposium on Field-Programmable Gate Arrays (FPGA), Seaside, CA, USA, February 2020.
|
|
|
|
Jawad Haj-Yahya, Yanos Sazeides, Mohammed Alser, Efraim Rotem, Onur Mutlu
|
|
|
|
|
|
PhD Defense
|
Practical Mechanisms for Reducing Processor-Memory Data Movement in Modern Workloads
|
|
|
|
Abstract Data movement between the memory system and computation units is one of the most critical challenges in designing high performance and energy-efficient computing system. The high cost of data movement is forcing architects to rethink the fundamental design of computer systems. Recent advances in memory design enable the opportunity for architects to avoid unnecessary data movement by performing Processing-In-Memory (PIM), also known as Near-Data Processing (NDP). While PIM can allow many data-intensive applications to avoid moving data from memory to the CPU, it introduces new challenges for system architects and programmers. Our goal in this thesis is to make PIM effective and practical in conventional computing systems. Toward this end, this thesis presents three major directions: (1) examining the suitability of PIM across key workloads, (2) addressing major system challenges for adopting PIM in computing systems, and (3) re-designing applications aware of PIM capability. In line with these three major directions, we propose a series of practical mechanisms to reduce processor-memory data movement in modern workloads.
|
|
|
|
|
CoNDA: Efficient Cache Coherence Support for Near-Data Accelerators, Amirali Boroumand, Saugata Ghose, Minesh Patel, Hasan Hassan, Brandon Lucia, Rachata Ausavarungnirun, Kevin Hsieh, Nastaran Hajinazar, Krishna T. Malladi, Hongzhong Zheng, and Onur Mutlu, ISCA, June 2019. Paper | Lightning Talk Video | Slides (pptx) (pdf)
|
Google Workloads for Consumer Devices: Mitigating Data Movement Bottlenecks, Amirali Boroumand, Saugata Ghose, Youngsok Kim, Rachata Ausavarungnirun, Eric Shiu, Rahul Thakur, Daehyun Kim, Aki Kuusela, Allan Knies, Parthasarathy Ranganathan, and Onur Mutlu, ASPLOS, March 2018. Paper | Lightning Talk Video | Full Talk Video (21 minutes) | Slides (pptx) (pdf)
|
LazyPIM: An Efficient Cache Coherence Mechanism for Processing-in-Memory, Amirali Boroumand, Saugata Ghose, Minesh Patel, Hasan Hassan, Brandon Lucia, Kevin Hsieh, Krishna T. Malladi, Hongzhong Zheng, and Onur Mutlu, IEEE Computer Architecture Letters (CAL), June 2016. Paper
|
|
|
|
|
|
Virtual Talks & Courses
|
We regularly post new videos of talks and lectures on our YouTube Channels. We want everyone to be able to access and benefit from our educational materials. We encourage you to subscribe, comment and give us feedback on our courses and talks! Please also help spread the word so that more people in the world can benefit from the free materials.
|
|
|
|
|
Recent Courses
|
|
|
|
|
|
|
|
|
|
We have introduced several hands-on project-based courses this semester. They aim to encourage independent experimentation, creative thinking and design, and explorative learning:
|
|
|
|
|
|
|
|
|
|
|
|
|
|
More of Onur Mutlu's Keynote Talks
|
Recent Talks - Onur Mutlu
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Selected Introductory Lectures
|
|
|
|
|
Selected Lectures: Computer Architecture ETH Fall 2020
|
|
|
|
|
|
|
|
|
|
|
Selected Conference Talks - SAFARI Group Members
|
|
|
|
|
|
|
|
|
Selected Open Source Releases
|
|
|
We have released several research artifacts and tools in 2020 -- all are available on GitHub: CMU-SAFARI
|
|
|
|
|
BEER determines an ECC code's parity-check matrix based on the uncorrectable errors it can cause. BEER targets Hamming codes that are used for DRAM on-die ECC but can be extended to apply to other linear block codes (e.g., BCH, Reed-Solomon).
|
Described in our MICRO 2020 paper:
|
|
|
|
|
The first and the only pre-alignment filtering algorithm that works efficiently and fast on modern CPU, FPGA, and GPU architectures. SneakySnake greatly (by more than two orders of magnitude) expedites sequence alignment calculation for both short (Illumina) and long (ONT and PacBio) reads.
|
|
PDNspot is a framework that models the three commonly-used power delivery network (PDN) architectures in modern client processors in multiple metrics of interest. PDNspot provides a versatile framework that enables multi-dimensional architecture-space exploration of modern processor PDNs.
|
Described in our MICRO 2020 paper:
|
|
|
|
AirLift is a tool that updates mapped reads from one reference genome to another. Unlike existing tools, It accounts for regions not shared between the two reference genomes and enables remapping across all parts of the references. Described in our preprint:
|
|
GenASM is an approximate string matching (ASM) acceleration framework for genome sequence analysis. GenASM is a fast, efficient, and flexible framework for both short and long reads, which can be used to accelerate multiple steps of the genome sequence analysis pipeline.
|
Described in our MICRO 2020 paper:
|
|
|
|
|
Source code of the sparse matrix kernels and utilities used to evaluate the schemes presented in our MICRO 2019 paper:
|
|
Apollo is an assembly polishing algorithm that attempts to correct the errors in an assembly. It can take multiple set of reads in a single run and polish the assemblies of genomes of any size. Described in our Bioinformatics paper:
|
|
|
|
|
|
Meet our members: on research, education and career
|
|
|
|
|
You recently won the Best Paper Award at MICRO, congratulations! Can you tell us about the significance of this paper?
|
This paper addresses the larger problem that hidden proprietary features implemented by DRAM manufacturers impede end-users from bringing out the best of DRAM technology. We believe BEER takes an important step towards bridging the gap between industry and end-users, starting by focusing on a key example of such features: on-die ECC. Our work discusses how and why on-die ECC limits third-party DRAM consumers and then introduces techniques that the consumers can use to overcome these limitations. We have released our tools in an open-source project and look forward to having the community use and extend them.
|
What were the biggest challenges for you during the writing and review process?
|
I would say that the biggest challenge we faced when writing this paper was to clearly articulate the problem of on-die ECC limiting third-party users. This includes both (i) describing how and why this limitation arises and (ii) providing concrete examples that the reader can relate to. We spent considerable effort in crafting these arguments such that both we and the reader have a clear understanding of the problem we tackle, our goal in this work, and the final value of our contributions.
|
|
|
|
|
|
You were a co-author on TRRespass, which recently won a Best Paper Award at IEEE S&P as well as a prestigious Pwnie Award for Most Innovative Research. What is the significance of this paper?
|
Shortly after the discovery of the RowHammer vulnerability of DRAM, DRAM vendors announced RowHammer-free DRAM devices that implement in-DRAM solutions to protect against RowHammer. However, in TRRespass, we find that such solutions, commonly referred to as Target Row Refresh (TRR), do not effectively protect against RowHammer attacks when many rows are hammered at the same time. We show that the RowHammer vulnerability is not only still intact on the current DDR4 devices, but it has also become worse due to technology node scaling.
|
How was your experience in collaborating with the Systems and Network Security Group at VU Amsterdam on this work?
|
I am glad that our combined effort with the Systems and Network Security Group at VU Amsterdam won us the Best Paper Award at IEEE S&P. It has been a great experience for me to collaborate with experts in hardware security. I hope there will be more such collaborations that result in impactful research.
|
Which tools did you use in this work?
I think SoftMC, our FPGA-based DRAM testing infrastructure, was one of the key enablers of this research. We used SoftMC to interface with DDR4 DRAM chips in a much more flexible way than anyone can do using commodity desktop and mobile systems. Specifically, we used SoftMC to communicate with DRAM chips using low-level DDR4 commands as opposed to using load/store instructions provided by typical instruction set architectures. In a way, SoftMC lets us be the memory controller and provides the flexibility of issuing any DDR4 command at any time, which is not possible with commodity systems.
An earlier version of SoftMC that supports DDR3 devices is open-source and can be accessed here. In 2017, we published a paper that describes the design of SoftMC in detail.
I am also involved in maintaining Ramulator, a cycle-accurate DRAM simulator that we describe in this paper, and Scarab, which is a cycle-accurate simulator for state-of-the-art multicore CPUs.
|
Pietro Frigo, Emanuele Vannacci, Hasan Hassan, Victor van der Veen, Onur Mutlu, Cristiano Giuffrida, Herbert Bos, and Kaveh Razavi, TRRespass: Exploiting the Many Sides of Target Row Refresh, Proceedings of the 41st IEEE Symposium on Security and Privacy (S&P), San Francisco, CA, USA, May 2020. Talk Video (17 minutes) | Lecture Video (59 minutes) | Lecture Slides (pptx) (pdf) Source Code Best paper award IEEE S&P Pwnie Award 2020 for Most Innovative Research
|
|
|
|
|
|
Can you tell us why it was important to revisit RowHammer now and how you extended the original study?
|
Since the first rigorous analysis of RowHammer on real DRAM chips in 2014, there have been many advances in DRAM technology including newer DRAM generations and protocols and reduced DRAM technology node sizes. While the original paper showed some correlation of more recently manufactured DRAM chips having a higher vulnerability to RowHammer bit flips, it was important to revisit RowHammer on more modern devices to see how the RowHammer vulnerability has worsened since then.
|
So are there good mitigation techniques for RowHammer, and have manufacturers been able to really solve the problem?
|
While our goal was not to determine whether mitigation mechanisms in modern devices prevented RowHammer bit flips, there have been many papers (e.g., TRRespass) that demonstrate weaknesses in existing mechanisms across many generations of DRAM. Until a patent or white paper is published by a DRAM manufacturer with proofs of RowHammer-free operation is released, I will continue to be skeptical, as DRAM manufacturer claims of RowHammer-free chips have been repeatedly refuted in the literature.
|
What is the overall significance of the paper?
|
We make two significant observations in this paper. First, the RowHammer vulnerability has significantly worsened in recent years, with the weakest observed chip exhibiting RowHammer bit flips after only 9600 accesses. Second, state-of-the-art academic proposals for RowHammer mitigation either are not scalable or have prohibitively large performance overheads in projected future devices given our observed trends of RowHammer vulnerability. Therefore, it is critical to continue research in more effective solutions to RowHammer.
|
Jeremie S. Kim, Minesh Patel, A. Giray Yaglikci, Hasan Hassan, Roknoddin Azizi, Lois Orosa, and Onur Mutlu, Revisiting RowHammer: An Experimental Analysis of Modern Devices and Mitigation Techniques, Proceedings of the 47th International Symposium on Computer Architecture (ISCA), Valencia, Spain, June 2020. Slides (pptx) (pdf) | Lecture Slides (pptx) (pdf) | Talk Video (20 minutes) | Lightning Talk Video (3 minutes) | Lecture Video (55 minutes)
|
|
|
|
|
|
|
|
Watch Damla's video interview here | Read the transcript here
|
Damla Senol Cali, Gurpreet S. Kalsi, Zulal Bingol, Can Firtina, Lavanya Subramanian, Jeremie S. Kim, Rachata Ausavarungnirun, Mohammed Alser, Juan Gomez-Luna, Amirali Boroumand, Anant Nori, Allison Scibisz, Sreenivas Subramoney, Can Alkan, Saugata Ghose, and Onur Mutlu, GenASM: A High-Performance, Low-Power Approximate String Matching Acceleration Framework for Genome Sequence Analysis, Proceedings of the 53rd International Symposium on Microarchitecture (MICRO), Virtual, October 2020.
|
|
|
|
|
How was your experience with SAFARI, and how do you think your PhD has benefitted from your stay in the group?
|
|
|
|
Regarding my experience with the SAFARI research group, I identify three important characteristics in the SAFARI group culture:
|
1. Collaboration : I realized that research can vastly benefit from close collaboration. Impactful and innovative research requires a lot of experience, a robust understanding of theoretical principles and deep knowledge surrounding the addressed problem. Considering the above, without the significant help and support from the other group members, who willingly and generously shared their expertise with me, providing me with rigorous feedback and offering their constructive criticism, my efforts would be much less impactful. Their valuable advice, consisting of concrete guidelines and useful methodologies helped me to work efficiently and stay focused in tackling my research obstacles.
|
2. Learning from group members : The best way to grow at a personal and professional level (both being key components of the PhD learning process) is to share knowledge and experience with others. In the context of academic research, this is particularly important for young students who have little prior research experience. Prof. Mutlu dedicates a lot of time providing feedback to his students, offering significant help by being engaged in frequent technical discussions with them, while at the same time encouraging them to develop their critical thinking skills and training them to evaluate, write and communicate their work efficiently and effectively. This attitude of mentoring and solidarity is commonplace in all SAFARI members (both senior and junior), who spend substantial effort on sharing feedback through discussing and interacting with each other within the group.
|
|
|
|
3. Motivation : Publishing a great paper is hard and time-consuming. Sometimes, the efforts invested in research may take long to come to fruition. For this reason, it is crucial for students to stay motivated and above all enjoy what they do. In SAFARI, motivation is achieved by: (i) carefully selecting the project students are working on to fit their interests and skills, (ii) interacting with highly-motivated group members (an inspiring work environment significantly elevates the student’s productivity), and (iii) being encouraged from your mentors and collaborators to always set high goals and persevere against all obstacles to attain them.
|
The aforementioned characteristics of the SAFARI group drove my mindset to be highly collaborative, made me be more open to receiving feedback and accepting criticism to improve my work, and be motivated to explore new fields/topics, without exclusively limiting myself to familiar ideas and concepts. As a result, my visit at SAFARI was an invaluable experience in my PhD, as it greatly helped me to acquire a proper research mindset by collaborating with a team of excellence to carry out high-quality research.
|
Would you recommend such a visit to other PhD students?
|
When I left Zurich, I had a new research mindset and a lot of motivation to pursue new research directions. During my stay, I greatly expanded my knowledge in the field of computer architecture (specifically in the topics of software/hardware cooperation, architectural support for synchronization and near-data-processing ) and acquired new perspectives in approaching research problems. Last but not least, my luggage was full of new experiences, collaborators and friends. Furthermore, I will be grateful to Prof. Mutlu for treating me as if I were his own PhD student and the people at SAFARI group for welcoming me and making me a part of their superb team. Considering the above, I would definitely and highly recommend other PhD students to visit the SAFARI research group.
|
|
|
|
|
|
You have been busy this past year, and have published quite a few papers. Your recent work, SneakySnake, was recently published in Bioinformatics. This is an important work in improving computations for genome analysis. Can you tell us more about the significance of this work, and what broader impacts you hope for it?
|
SneakySnake is one of the projects that I enjoyed the most working on. We try in this work to significantly reduce the time spent on finding the similarities and differences between two genomic sequences without sacrificing solution optimality. Finding the similarities and differences between two sequences is a well-known computer science problem, called approximate string matching (ASM), which is solved using computationally expensive algorithms.
|
SneakySnake quickly finds the sequence pairs that have a large (greater than a user-defined threshold) number of differences and prevents applying computationally expensive algorithms for these sequence pairs, as such sequence pairs are usually not useful for genomic studies. SneakySnake is inspired by the single net routing (SNR) problem in VLSI design that was introduced in 1976. SneakySnake is the first work that proposes to convert the ASM problem into an instance of the SNR problem, which provides several key benefits as we discussed in the paper, and proposes a new efficient algorithm for comparing genomic sequences at scale.
|
SneakySnake is very beneficial for analyzing both short (e.g., Illumina) and long (e.g., nanopore) sequences as it accelerates the analysis of genomic sequences by up to two orders of magnitude compared to the state-of-the-art algorithms. SneakySnake works efficiently and fast on modern CPU, FPGA, and GPU architectures, which can potentially enable new applications of genome sequencing such as rapid surveillance of disease outbreaks including Ebola and COVID-19, near-patient testing, and bringing precision medicine to remote locations, without the need for large infrastructure.
|
One of the Bioinformatics journal’s reviewers states that: “SneakySnake is a valuable contribution to bioinformatics and it was innovative to reduce the ASM problem to the SNR problem in VLSI CAD”.
|
You also recently published Accelerating Genome Analysis, which reviews the improvements made in hardware accelerators for genome analysis. What are your take away messages from this paper, and what do you see as future priorities in hardware improvements for genome analysis?
|
Most speedup comes from parallelism enabled by novel architectures and algorithms. We need to develop acceleration solutions that exploit new efficient hardware-aware algorithms, hardware/software co-design, and hardware accelerators to achieve a high degree of parallelism.
|
Accelerating the entire genome analysis pipeline is important. Accelerating only a single step of genome analysis is not an effective acceleration approach as it limits the overall achieved speedup according to Amdahl’s Law.
|
Genome analysis is currently heavily bottlenecked by data movement. We need to reduce the high amount of data movement that takes place during genome analysis. Moving data (1) between compute units and main memory, (2) between multiple hardware accelerators, and (3) between the sequencing machine and the computer performing the analysis incurs high costs in terms of execution time and energy. These costs are a significant barrier to enabling efficient analysis that can keep up with sequencing technologies.
|
The need for flexible hardware architectures. We need to develop flexible hardware architectures that do not conservatively limit the range of supported parameter values at design time. Rapid changes in sequencing technologies (e.g., those that result in high sequencing error rates and longer read lengths) can quickly make specialized hardware with restricted parameter values obsolete.
|
The need for new genomic data formats. We need to adapt existing genomic data formats for hardware accelerators or develop more efficient file formats to maximize the benefits of hardware accelerators and reduce resource utilization.
|
Looking into the future, building a genome sequencing machine that provides the entire genome as a single string, rather than its short subsequences, might be possible. However, we believe that the need for hardware acceleration of whole-genome analysis will continue to remain necessary. We also believe performing genome analysis inside the sequencing machine itself can significantly improve efficiency by eliminating sequencer-to-computer data movement.
|
Your work has many topical applications that are highly relevant to society, including COVID modeling. Can you talk a bit about this, and your future research directions?
|
As the entire world is largely negatively impacted by the recent COVID-19 outbreak, we believe that everyone can help to end this pandemic based on their skills, expertise, and available resources. At SAFARI research group, we are helping with two main directions.
|
We are working on developing an accurate and configurable prediction model that evaluates the existing mitigation measures that the government applies in a region and provides suggestions on what strength the future mitigation measures should be. We are quantifying the spread of COVID-19 in Switzerland (as a use-case) by calculating the daily reproduction number of COVID-19, which quantifies how many people are infected on average by an infected person. The reproduction number is directly affected by the mitigation measures that the government applies to a region. We are also considering other important factors such as daylight temperature that significantly affect the spread of COVID-19 as we observed during the year 2020.
|
We are also working on developing new algorithms and hardware accelerators that perform fast and accurate metagenomic profiling for assessing microbial diversity, identifying potential new species, and investigating microbiomes associated with COVID-19 and other diseases. Performing genomic tests at scale during a pandemic highlights the dire need for building efficient specialized hardware that is both scalable and portable to enable genome analysis anywhere and anytime. We hope that the progress we make in this direction will also enable new applications that benefit human life and society.
|
Mohammed Alser, Taha Shahroodi, Juan-Gomez Luna, Can Alkan, and Onur Mutlu, SneakySnake: A Fast and Accurate Universal Genome Pre-Alignment Filter for CPUs, GPUs, and FPGAs, Bioinformatics, December 2020. Paper PDF | Paper link Bioinformatics | Source Code
Mohammed Alser, Zulal Bingol, Damla Senol Cali, Jeremie Kim, Saugata Ghose, Can Alkan, and Onur Mutlu, Accelerating Genome Analysis: A Primer on an Ongoing Journey, IEEE MICRO, September/October 2020. Paper | Slides (pptx) (pdf)
|
|
|
|
|
You recently joined the group remotely. Can you tell us what you are working on, and how your experience with collaborating with SAFARI has been?
|
|
|
|
I joined SAFARI in September 2020 as an Affiliated Researcher. In my former research effort and in my Ph.D. thesis, I improved hardware accelerators' energy-efficiency. More recently, in collaboration with Prof. Onur Mutlu, I proposed an effective Undervolting technique for FPGA-based Convolutional Neural Network (CNN) accelerators, which delivered more than 3X energy-efficiency gain. In my opinion, this work, published in DSN'2020, opened a new door for using such undervolting techniques in accelerators especially in power-constrained domains like mobile environments. With this experience as a starting point and jointly with other SAFARI Groups' members, I have started exploring the energy-efficiency, resiliency, and security aspects of novel accelerator architectures like Processing-near & in-Memory systems. I believe that the cutting-edge research in the group, which I am thrilled to be part of, plays an important role in enabling such architectures in future embedded and HPC systems.
|
And how has it been working remotely with the group?
|
I started working with the group remotely, right in the middle of the Coronavirus pandemic, which created a Volatile, Uncertain, Complex, and Ambiguous (VUCA) condition. Under this condition, starting to work with new people, in a new atmosphere, and on new projects could be challenging. However, this phase was quite smooth for me, thanks to the group’s friendly atmosphere, the warm welcome of Prof. Onur Mutlu and other group members, and the projects’ collaborative nature. In this way, I see online meetings as a key way to stay motivated to explore and build new ideas in collaboration with other members of the group.
|
Behzad Salami, Erhan Baturay Onural, Ismail Emir Yuksel, Fahrettin Koc, Oguz Ergin, Adrian Cristal Kestelman, Osman S. Unsal, Hamid Sarbazi-Azad, and Onur Mutlu, An Experimental Study of Reduced-Voltage Operation in Modern FPGAs for Neural Network Acceleration, Proceedings of the 50th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), Valencia, Spain, June 2020.
|
|
|
|
|
Haiyu Mao joined SAFARI in October as a postdoc.
|
When you arrived, most of us were working remotely due to Corona, which must have been quite challenging for you, having just arrived from China. Can you tell us about your first impressions in SAFARI, and your impressions now, after a few months with SAFARI?
|
|
|
|
When I arrived in September, SAFARI happened to move to the new office. It was a little challenging for me to start during the COVID-19 time. However, I felt very happy to receive the help from Prof. Onur Mutlu and SAFARI group members. Onur met me in person. We discussed the projects that I was interested in. He gave me a lot of suggestions on how to start the research and how to do high-impact research. I was very impressed with Onur’s serious attitude towards research and teaching, which drove me to work hard, think big, and aim high. Tracy helped me a lot with my setup at ETH and the new office, which enabled me to start the research in a short time. Other group members, Nika, Jisung, Lois, Hasan, Minesh, Geraldo, and so on, helped me a lot with the setup. I am very happy to have these friendly and helpful group members.
|
Research: Since we have lots of group meetings and brainstorming, which has continued over Zoom, I didn’t feel much inconvenience with regard to collaborating during COVID-19. I am getting to know the group members and their research through these meetings. I am glad to work with our brilliant and self-motivated group members. I hope I can have several high-impact research outcomes in such an amazing and collaborative group.
|
Teaching: I was very nervous about the teaching at the beginning because of my lack of teaching experience. After three months, I already feel much better with the help of other TAs.
|
Can you tell us what you are working on, and what your future research plans/directions are?
|
My research interests mainly include non-volatile memories, processing-in-memory, memory security, and machine learning. I am now working on the security of processing-in-memory and heterogeneous processing-in-memory architectures. Besides this, I am also interested in neural network training in processing-in-memory architectures. I hope I can contribute a lot to the processing-in-memory research and bring these ideas into industry to have wonderful commercial chips.
|
|
|
|
|
You had several papers published this year, can you tell us more about the significance of each of these papers?
|
|
|
|
I have published multiple papers on energy efficiency and power management this year.
In our HPCA 2020 paper that introduces ODRIPS, i.e., optimized-deepest-runtime-idle-power state, we developed techniques for reducing the connected-standby energy consumption of mobile devices. ODRIPS dynamically: 1) offloads the monitoring of wake-up events to low-power off-chip circuitry, which enables turning off all of the processor’s clock sources, 2) offloads all of the processor’s input/output functionality off-chip and power gates the corresponding on-chip input/output functions, and 3) transfers the processor’s context to a secure memory region inside DRAM, which eliminates the need to store the context using high-leakage on-chip SRAMs, thereby reducing leakage power. Overall, our proposed three-pronged strategy reduces platform average power in connected-standby mode by 22%.
|
In our ISCA 2020 paper that introduces SysScale, we proposed the first work to enable coordinated and highly-efficient dynamic voltage and frequency scaling (DVFS) across all system-on-chip (SoC) domains to increase the energy efficiency of mobile SoCs. SysScale introduces the ability to redistribute the total power budget across all SoC domains according to the performance demands of each domain. We implement SysScale on the Intel Skylake SoC for mobile devices. On a 2-core Skylake with a 4.5W TDP, SysScale improves the performance of SPEC CPU2006 and 3DMark workloads by up to 16% and 8.9% (9.2% and 7.9% on average), respectively.
|
In our MICRO 2020 paper that introduces FlexWatts, we design a novel adaptive hybrid Power Delivery Network (PDN) that maintains high efficiency and high performance in metrics of interest in client processors across a wide spectrum of power consumption and workloads. To our knowledge, FlexWatts is the first hybrid PDN to use two types of on-chip voltage regulators (IVR and LDO) to simultaneously leverage the advantages of both. During this project, we also develop a versatile framework, PDNspot, that enables multi-dimensional architecture-level exploration of modern processor PDNs. To our knowledge, PDNspot is the first tool that can evaluate the effects of multiple PDN parameters, TDP, and workload characteristics on prominent system metrics such as energy consumption, performance, board area, and bill of materials (BOM). We have open-sourced PDNspot. For a 4W thermal design power (TDP) processor, FlexWatts improves the average performance of the SPEC CPU2006 and 3DMark06 workloads by 22% and 25%, respectively. For battery life workloads, FlexWatts reduces the average power consumption of video playback by 11% across all tested TDPs (4W–50W).
|
What were the biggest challenges in publishing these papers (if any)?
|
All our three recent works focus on optimizing the energy-efficiency of modern processors from three different angles by optimizing 1) idle energy consumption, 2) dynamic energy consumption, and 3) power delivery networks. Proposing improvements to these highly-optimized commodity processor components is very challenging. It requires a deep understanding of modern processor power management architecture and bottlenecks. For example, in ODRIPS the baseline processors already consume a few milliwatts in the deepest idle state. Reducing this already-low power consumption requires further out-of-the-box thinking. We introduce the idea of dynamically offloading the processor context into DRAM, which saves the entire processor context once the processor is idle.
|
In SysScale, we observed that the power budget of the processor is inefficiently managed between various SoC domains. The most challenging part was to figure out how to dynamically redistribute the power-budget between domains with minimal overhead. Therefore, building the transition flow and the performance prediction algorithm were the main challenging parts.
In FlexWatts, we observed that the commonly-used power delivery networks in client processors have multiple pros and cons with respect to multiple metrics. The challenging part is to develop a model that accurately and efficiently quantifies these metrics. To this end, we developed PDNspot. Next, we observed the need for a hybrid PDN that provides the benefits of the commonly-used PDNs. The challenging part of this PDN is to make it low overhead in terms of area and cost while maintaining low transition time between the different modes of operation of the hybrid PDN.
|
What are you working on next?
|
I’m working on multiple projects related to energy-efficiency and hardware security. In particular, we observed a fundamental bottleneck in the modern display subsystem of modern processors and we are working to reduce this bottleneck which will save significant energy for essential workloads such as video streaming (which probably almost all of us rely on today). Moreover, we found that there are many security vulnerabilities in the energy management mechanisms of modern processors. We are working on demonstrating security attacks on these mechanisms and propose new architectures to make these processors more secure.
|
Jawad Haj-Yahya, Yanos Sazeides, Mohammed Alser, Efraim Rotem, Onur Mutlu, Techniques for Reducing the Connected-Standby Energy Consumption of Mobile Devices, Proceedings of the 26th International Symposium on High-Performance Computer Architecture (HPCA), San Diego, CA, USA, February 2020.
|
Jawad Haj-Yahya, Mohammed Alser, Jeremie Kim, A. Giray Yaglikci, Nandita Vijaykumar, Efraim Rotem, and Onur Mutlu, SysScale: Exploiting Multi-domain Dynamic Voltage and Frequency Scaling for Energy Efficient Mobile Processors, Proceedings of the 47th International Symposium on Computer Architecture (ISCA), Valencia, Spain, June 2020.
|
Jawad Haj-Yahya, Mohammed Alser, Jeremie S. Kim, Lois Orosa, Efraim Rotem, Avi Mendelson, Anupam Chattopadhyay, and Onur Mutlu, FlexWatts: A Power- and Workload-Aware Hybrid Power Delivery Network for Energy-Efficient Microprocessors, Proceedings of the 53rd International Symposium on Microarchitecture (MICRO). Virtual, October 2020.
|
|
|
|
|
|
|
|
|