Presentations given by SAFARI group members (not including conference publications talks — these can be found on Onur Mutlu’s Publications page and Talks page).
- Juan Gómez-Luna, Izzat El Hajj, Ivan Fernandez, Christina Giannoula, Geraldo F. Oliveira, Onur Mutlu, Benchmarking Memory-Centric Computing Systems: Analysis of Real Processing-in-Memory Hardware, SRC TECHCON 2022, Austin, TX, Sept 18-20, 2022.
[Talk 20min: Slides (pptx) (pdf)]
[Talk 16min: Slides (pptx) (pdf)]
[Talk final: Slides (pptx)(pdf)]
Related Papers:
Gómez-Luna et al., “Benchmarking Memory-Centric Computing Systems: Analysis of Real Processing-in-Memory Hardware“, CUT 2021.
Gómez-Luna et al., “Benchmarking a New Paradigm: Experimental Analysis and Characterization of a Real Processing-in-Memory System“, IEEE Access 2022.
IEEE Computer Society Annual Symposium on VLSI, Pafos, Cyprus, July 4-6, 2022
Special Session 3: In Memory Processing I, Session Chair: Juan Gomez Luna, ETH Zurich
- Juan Gomez Luna,
“Introduction: In-Memory Processing ISVLSI 2022 Special Session“,
[Slides (pptx) (pdf)]Related Papers:
“A Modern Primer on Processing in Memory”
“Processing Data Where It Makes Sense: Enabling In-Memory Computation”
“Benchmarking a New Paradigm: Experimental Analysis and Characterization of a Real Processing-in-Memory System”
“Benchmarking Memory-Centric Computing Systems: Analysis of Real Processing-in-Memory Hardware”
- Saugata Ghose (University of Illinois Urbana-Champaign),
“The Road to Widely Deploying Processing-In-Memory: Challenges and Opportunities”,
[Slides (pdf)]Related Papers:
“Processing-in-Memory: A Workload-Driven Perspective”
“Enabling the Adoption of Processing-in-Memory: Challenges, Mechanisms, Future Research Directions”
- Geraldo Francisco De Oliveira Junior, Juan Gomez Luna, Saugata Ghose, Onur Mutlu,
“Methodologies, Workloads, and Tools for Processing-In-Memory: Enabling the Adoption of Data-Centric Architectures”, [Slides (pptx) (pdf)]
Related Papers:
“SIMDRAM: An End-to-End Framework for Bit-Serial SIMD Computing in DRAM”
“DAMOV: A New Methodology and Benchmark Suite for Evaluating Data Movement Bottlenecks”
- Ataberk Olgun, Juan Gomez Luna, Konstantinos Kanellopoulos, Behzad Salami, Hasan Hassan, Oguz Ergin, Onur Mutlu,
“PiDRAM: An FPGA-Based Framework for End-To-End Evaluation of Processing-In-DRAM Techniques”,[Slides (pptx) (pdf)]
Related Paper:
“PiDRAM: A Holistic End-to-end FPGA-based Framework for Processing-in-DRAM”
Special Session 4: In Memory Processing II, Session Chair: Juan Gomez Luna, ETH Zurich, Switzerland
- Geraldo Francisco De Oliveira Junior, Saugata Ghose, Juan Gomez Luna, Onur Mutlu,
“Heterogeneous Data-Centric Architectures for Modern Data-Intensive Applications: Case Studies in Machine Learning and Databases”,
[Slides (pptx) (pdf)]
Related Papers:
“Google Neural Network Models for Edge Devices: Analyzing and Mitigating Machine Learning Inference Bottlenecks”
“Polynesia: Enabling High-Performance and Energy-Efficient Hybrid Transactional/Analytical Databases with Hardware/Software Co-Design”
- Ivan Fernandez (University of Malaga & ETH Zurich), Ricardo Quislant, Christina Giannoula, Mohammed Alser, Juan Gomez Luna, Eladio D Gutierrez, Oscar Plata, Onur Mutlu,
“Exploiting Near-Data Processing to Accelerate Time Series Analysis”,
[Slides (pptx) (pdf)]
Related Paper:
“NATSA: A Near-Data Processing Accelerator for Time Series Analysis”
- Nika Mansouri Ghiasi, Jisung Park, Harun Mustafa, Jeremie Kim, Ataberk Olgun, Arvid Gollwitzer, Damla Senol Cali, Can Firtina, Haiyu Mao, Nour Almadhoun Alserr, Rachata Ausavarungnirun, Nandita Vijaykumar, Mohammed Alser, Onur Mutlu,
“GenStore: In-Storage Filtering of Genomic Data for High-Performance and Energy-Efficient Genome Analysis”,
[Slides (pptx) (pdf)]
Related Paper:
“GenStore: A High-Performance and Energy-Efficient In-Storage Computing System for Genome Sequence Analysis”
- Christina Giannoula (National Technical University of Athens & ETH Zurich), Ivan Fernandez, Juan Gomez-Luna, Nectarios Koziris, Georgios Goumas, Onur Mutlu,
“SparseP: Efficient Sparse Matrix Vector Multiplication on Real Processing-In-Memory Architectures”,[Slides (pptx) (pdf)]
Related Paper:
“SparseP: Towards Efficient Sparse Matrix Vector Multiplication on Real Processing-In-Memory Architectures”
- Juan Gomez Luna, Yuxin Guo, Sylvan Brocard, Julien Legriel, Remy Cimadomo, Geraldo Oliveira, Gagandeep Singh, Onur Mutlu,
“Machine Learning Training on a Real Processing-In-Memory System”,
[Slides (pptx) (pdf)]
Related Paper:
“Machine Learning Training on a Real Processing-in-Memory System”
-
Juan Gómez Luna,
“Enabling the Processing-in-Memory Paradigm for Future Computing Systems”
Talk at Universidad de Córdoba, 16 March 2022 [Slides (pptx) (pdf)]
[Talk Video] - Mohammed Alser,
“A Roadmap for Fast and Efficient Genome Analysis”
Talk at the University of Tokyo, Tokyo, 19 Dec 2019 [Slides (pptx) (pdf)]
Talk at the University of Tokyo Shirokanedai Campus, Tokyo, 20 Dec 2019 [Slides (pptx) (pdf)]
[Talk Video]
- Mohammed Alser,
“Accelerating Genome Analysis Using New Algorithms and Hardware Designs”
Talk at Preferred Networks, Tokyo, 16 Dec 2019 [Slides (pptx) (pdf)]
Talk at RIKEN Center for Computational Science, Kobe, 17 Dec 2019 [Slides (pptx) (pdf)]
Talk at the University of Tokyo Kashiwa Campus, Tokyo, 18 Dec 2019 [Slides (pptx) (pdf)]
- Can Firtina, Jeremie S. Kim, Mohammed Alser, Damla Senol Cali, A. Ercument Cicek, Can Alkan, and Onur Mutlu,
“Apollo: A Sequencing-Technology-Independent, Scalable, and Accurate Assembly Polishing Algorithm”
Poster presentation at the Swiss Genomics Forum 2019, Geneva, 27 Sept 2019.
[Poster (pptx) (pdf)]
[Paper, arXiv (pdf)]
[Source code for Apollo]
- Mohammed Alser, Can Alkan, Onur Mutlu,
“SneakySnake: A New Fast and Highly Accurate Pre-Alignment Filter on CPU and FPGA for Accelerating Sequence Alignment”
Poster presentation at the Swiss Genomics Forum 2019, Geneva, 27 Sept 2019.
[Poster (pptx) (pdf)]
[Source code for SneakySnake]
- Saugata Ghose,
“Modeling and Mitigating Early Retention Loss and Process Variation in 3D NAND Flash”
Talk at the Flash Memory Summit 2019, Santa Clara, CA, 6-8 August 2019.
[Slides (pptx) (pdf)]
[Original Paper]
- Saugata Ghose,
“FLIN: Enabling Fairness and Enhancing Performance in Modern NVMe Solid State Drives”
Talk at the Flash Memory Summit 2019, Santa Clara, CA, 6-8 August 2019.
[Slides (pptx) (pdf)]
[Original Paper]
[Source code for MQSim]
- Can Firtina, Jeremie S. Kim, Mohammed Alser, Damla Senol Cali, A. Ercument Cicek, Can Alkan, and Onur Mutlu,
“Apollo: A Sequencing-Technology-Independent, Scalable, and Accurate Assembly Polishing Algorithm”
Poster presentation at the 27th Conference on Intelligent Systems for Molecular Biology (ISMB) and the 18th European Conference on Computational Biology (ECCB), Basel, 21-25 July 2019.
[Poster (pptx) (pdf)]
- Damla Senol Cali, Gurpreet S. Kalsi, Lavanya Subramanian, Can Firtina, Anant V. Nori, Jeremie S. Kim, Zulal Bingöl, Rachata Ausavarungnirun, Mohammed Alser, Juan Gomez-Luna, Amirali Boroumand, Allison Scibisz, Sreenivas Subramoney, Can Alkan, Saugata Ghose, and Onur Mutlu,
“BitMAC: An In-Memory Accelerator for Bitvector-Based Sequence Alignment of Both Short and Long Genomic Reads”
Poster presentation at the 27th Conference on Intelligent Systems for Molecular Biology (ISMB) and the 18th European Conference on Computational Biology (ECCB), Basel, 21-25 July 2019.
[Poster (pptx) (pdf)]
- Mohammed Alser, Can Alkan, Onur Mutlu,
“SneakySnake: A New Fast and Highly Accurate Pre-Alignment Filter on CPU and FPGA for Accelerating Sequence Alignment”
Poster presentation at the 27th Conference on Intelligent Systems for Molecular Biology (ISMB) and the 18th European Conference on Computational Biology (ECCB), Basel, 21-25 July 2019.
[Poster (pptx) (pdf)]