[vc_row tm_bgimagefixed=”” break_in_responsive=”991″ tm_zindex=”2″ full_width=”stretch_row” tm_responsive_css=”60233685|colbreak_no|||||||||colbreak_no|||||55px||25px||colbreak_no||||||||||colbreak_no|||||||||” css=”.vc_custom_1626073880162{padding-top: 111px !important;padding-bottom: 0px !important;}”][vc_column reduce_extra_padding=”991″ tm_responsive_css=”22114509|colbreak_no|||||||||colbreak_no|||||||||colbreak_no||||||||||colbreak_no|||||||||” css=”.vc_custom_1626073647852{padding-right: 100px !important;}”][vc_raw_html]JTNDYSUyMG5hbWUlM0QlMjJrZXlub3RlczIlMjIlMjBzdHlsZSUzRCUyMnBvc2l0aW9uJTNBJTIwYWJzb2x1dGUlM0IlMjAlMjBsZWZ0JTNBJTIwMHB4JTNCJTIwJTIwdG9wJTNBJTIwLTEwMHB4JTNCJTIyJTNFJTNDJTJGYSUzRQ==[\/vc_raw_html]
<\/div><\/div><\/div><\/div><\/section><\/div> [vc_single_image image=”3946″ style=”vc_box_circle_2″][\/vc_column][vc_column width=”1\/2″][vc_tta_accordion color=”grey” c_icon=”chevron” c_position=”right” active_section=”1″ collapsible_all=”true”][vc_tta_section title=”Abstract” tab_id=”1629234536160-db282339-36e7″][vc_column_text]Recent years have witnessed a surge of interest in applying machine learning to the design of networked systems. I will discuss my recent efforts along these lines in the context of two fundamental challenges: routing and congestion control. Specifically, I will present a general framework for online-learning-based Internet congestion control, and also a novel, deep-learning-based approach to optimizing traffic flow between data centers. Time permitting, I will also discuss recent results on how the safe deployment of such learning-augmented systems can be accommodated.[\/vc_column_text][\/vc_tta_section][vc_tta_section title=”Bio” tab_id=”1629234536247-1ed2440d-7944″][vc_column_text]Michael Schapira\u00a0<\/strong><\/b>is professor of Computer Science at Hebrew University. His research focuses on the design and analysis of (Inter)network architectures and protocols and, in particular, on the interface of networking and machine learning.\u00a0 Prior to joining Hebrew U, he was a visiting scientist at Google NYC\u2019s Infrastructure Networking Group and a postdoctoral researcher at UC Berkeley, Yale University, and Princeton University. He is a recipient of the Wolf Foundation\u2019s Krill Prize, faculty awards from Microsoft, Google, and Facebook, IETF\/IRTF Applied Networking Research Prizes, and the IEEE Communications Society William R. Bennett Prize.[\/vc_column_text][\/vc_tta_section][\/vc_tta_accordion][\/vc_column][\/vc_row][vc_row tm_bgimagefixed=”” break_in_responsive=”991″ tm_zindex=”2″ full_width=”stretch_row” tm_responsive_css=”60233685|colbreak_no|||||||||colbreak_no|||||55px||25px||colbreak_no||||||||||colbreak_no|||||||||” css=”.vc_custom_1641928628140{padding-top: 111px !important;padding-bottom: 0px !important;}”][vc_column width=”1\/2″ tm_responsive_css=”31574345|colbreak_no|||||||||colbreak_no|||||15px||||colbreak_no||||||||||colbreak_no|||||||||” el_class=”tm-reset-all-left-991″] <\/div><\/div><\/div><\/div><\/section><\/div> [vc_single_image image=”3966″ style=”vc_box_circle_2″][\/vc_column][vc_column width=”1\/2″][vc_tta_accordion color=”grey” c_icon=”chevron” c_position=”right” active_section=”1″ collapsible_all=”true”][vc_tta_section title=”Abstract” tab_id=”1629235035324-d13fd0d1-c9f1″][vc_column_text]More and more data-intensive applications, e.g., micro-service architectures and machine learning workloads, move from on-premise deployments to the cloud. Traditional cloud security mechanisms focus on strict isolation, but these applications require the efficient yet secure sharing of data between components and services. In this talk, I will explore how we can use a new hardware security feature, memory capabilities, to design a cloud stack that bridges the tension between isolation and sharing. Memory capabilities constrain memory accesses, and they can be used to provide a VM-like isolation mechanism, cVMs, that can share data more efficiently than containers. Memory capabilities can also increase memory efficiency in the cloud by safely de-duplicating application components. I will discuss our experience in building a cloud stack using memory capabilities on the CHERI architecture, as implemented by Arm’s Morello hardware.[\/vc_column_text][\/vc_tta_section][vc_tta_section title=”Bio” tab_id=”1629235035427-a14098de-d58a”][vc_column_text]Peter Pietzuch<\/strong> is a Professor of Distributed Systems at Imperial College London, where he leads the Large-scale Data & Systems (LSDS) group (https:\/\/lsds.doc.ic.ac.uk<\/a>). His research work focuses on the design and engineering of scalable, reliable and secure data-intensive software systems, with a particular interest in performance, data management and security issues. In addition, he is the Director of Research in the Department of Computing and a Co-Director for Imperial\u2019s I-X initiative on AI, data and digital (https:\/\/ix.imperial.ac.uk<\/a>). Recently, he has served as the Chair of the ACM SIGOPS European Chapter (EuroSys) and the Programme Committee Chair for ICDCS 2018. Before joining Imperial College London, he was a post-doctoral Fellow at Harvard University. He holds PhD and MA degrees from the University of Cambridge.[\/vc_column_text][\/vc_tta_section][\/vc_tta_accordion][\/vc_column][\/vc_row][vc_row tm_bgimagefixed=”” break_in_responsive=”991″ tm_zindex=”2″ full_width=”stretch_row” tm_responsive_css=”60233685|colbreak_no|||||||||colbreak_no|||||55px||25px||colbreak_no||||||||||colbreak_no|||||||||” css=”.vc_custom_1646216025783{padding-top: 111px !important;padding-bottom: 0px !important;}”][vc_column width=”1\/2″ tm_responsive_css=”31574345|colbreak_no|||||||||colbreak_no|||||15px||||colbreak_no||||||||||colbreak_no|||||||||” el_class=”tm-reset-all-left-991″] <\/div><\/div><\/div><\/div><\/section><\/div> [vc_single_image image=”3995″ style=”vc_box_circle_2″][\/vc_column][vc_column width=”1\/2″][vc_tta_accordion color=”grey” c_icon=”chevron” c_position=”right” active_section=”1″ collapsible_all=”true”][vc_tta_section title=”Abstract” tab_id=”1629274246379-90f8241e-bd50″][vc_column_text]Deterministic databases provide strong serializability while avoiding concurrency-control related aborts by establishing a serial ordering of transactions before their execution. Other benefits include good distributed transaction scaling, and simpler replication and failure recovery since transactions can be replayed deterministically. However, prior deterministic databases scaled poorly under skewed and contended transactional workloads, and the capacity of main memory typically limited their size.<\/p>\n In this talk, I will discuss our work on Caracal, a novel deterministic database that performs well under both skew and contention. Like prior designs, we batch transactions into epochs and execute the transactions in an epoch in a predetermined order. However, we eschew partitioning, commonly used to avoid contention, in favour of a shared-memory design that handles skewed workloads more effectively. We manage contention both during the concurrency-control initialization phase that establishes the execution order for a batch of transactions and during the execution phase, with two novel optimizations that are enabled by the batched deterministic execution model. With these optimizations, Caracal scales well and outperforms existing deterministic schemes in most workloads by 1.9x to 9.7x.<\/p>\n We further show how to integrate non-volatile main memory (NVMM) into Caracal to support larger data sets at a lower cost per gigabyte, and to support faster failure recovery. We describe a novel dual-version checkpointing scheme that takes advantage of deterministic execution, epoch-based processing, and NVMM’s byte addressability to avoid persisting all updates to NVMM.[\/vc_column_text][\/vc_tta_section][vc_tta_section title=”Bio” tab_id=”1629274246546-678008ee-1cbf”][vc_column_text]Angela Demke Brown<\/strong> is a Full Professor in the Department of Computer Science at the University of Toronto. She received her MSc from the University of Toronto and her PhD from Carnegie Mellon University, where her thesis work on compiler-based memory management for out-of-core applications received the Carnegie Mellon Doctoral Dissertation Award and was nominated for the ACM Doctoral Dissertation Award. Her research interests span operating systems, file systems, databases, and programming language runtimes with a focus on the performance and reliability of memory and storage management. Her work has received Best Paper awards at USENIX OSDI, USENIX FAST, and IEEE IPDPS. Dr. Brown was an IBM Faculty Fellow and Visiting Scientist from 2004 to 2007; in 2005 her research group received the IBM Centre for Advanced Studies \u201cTeam of the Year\u201d award. She has previously held a NetApp Faculty Fellowship and was a Visiting Researcher at Microsoft Research UK in 2015-16. She has served as Program co-Chair for OSDI, FAST and HotStorage, as well serving on the USENIX Board of Directors, and as an Associate Editor for ACM Transactions on Computer Systems. She is a member of ACM and USENIX.[\/vc_column_text][\/vc_tta_section][\/vc_tta_accordion][\/vc_column][\/vc_row][vc_section][vc_row tm_bgimagefixed=”” break_in_responsive=”991″ tm_zindex=”2″ full_width=”stretch_row” tm_responsive_css=”60233685|colbreak_no|||||||||colbreak_no|||||55px||25px||colbreak_no||||||||||colbreak_no|||||||||” css=”.vc_custom_1626073880162{padding-top: 111px !important;padding-bottom: 0px !important;}”][vc_column reduce_extra_padding=”991″ tm_responsive_css=”22114509|colbreak_no|||||||||colbreak_no|||||||||colbreak_no||||||||||colbreak_no|||||||||” css=”.vc_custom_1626073647852{padding-right: 100px !important;}”][vc_raw_html]JTNDYSUyMG5hbWUlM0QlMjJmdWxsLXByb2dyYW0lMjIlMjBzdHlsZSUzRCUyMnBvc2l0aW9uJTNBJTIwYWJzb2x1dGUlM0IlMjAlMjBsZWZ0JTNBJTIwMHB4JTNCJTIwJTIwdG9wJTNBJTIwLTEwMHB4JTNCJTIyJTNFJTNDJTJGYSUzRQ==[\/vc_raw_html][vc_separator css=”.vc_custom_1629274213962{margin-top: -30px !important;margin-bottom: 20px !important;}”] 09:00<\/b> Welcome and registration<\/span><\/p>\n 09:40<\/b> Opening session<\/b><\/p>\n 10:00<\/b> Keynote <\/b>#1: Towards Learning-Powered Networked Systems,<\/em> Michael Schapira<\/span><\/strong>, Hebrew University of Jerusalem<\/b><\/p>\n 11:00<\/b> Break<\/span><\/p>\n 11:20<\/b> Session A: File Systems<\/b><\/p>\n Chair: Gala Yadgar (Technion<\/em>)<\/strong><\/p>\n 12:20<\/b>\u00a0Lunch<\/span><\/p>\n 13:40<\/b> Session B: KV stores<\/b><\/p>\n Chair: Sam H. Noh (Virginia Tech<\/em>)<\/strong><\/b><\/p>\n 14:40 till ~ 21:30 <\/b>Social Event – Caesarea tour and dinner (15:00-16:00, 16:00-17:00 – Computer Science Escape Room alternative)<\/p>\n 08:45<\/b>\u00a0Welcome and registration<\/span><\/p>\n 09:15<\/b>\u00a0Keynote #2: Improving Cloud Security with Hardware Memory Capabilities, Peter Pietzuch<\/span> (Imperial College London)<\/b><\/p>\n 10:15<\/b>\u00a0Break<\/p>\n 10:35<\/b>\u00a0Session C: SSDs<\/b><\/p>\n Chair: Aviad Zuck (Technion<\/em>)<\/b><\/p>\n 11:35 <\/b>break<\/p>\n 11:50 Session D: Misc<\/strong><\/b><\/p>\n Chair: Orna Agmon Ben-Yehuda (CRI, Haifa University<\/em>)<\/strong><\/b><\/p>\n 12:50 <\/b>Lunch<\/p>\n 14:00<\/b>\u00a0Session E: Highlights<\/strong><\/p>\n Chair: Shir Landau-Feibish (Open University Israel<\/em>)<\/strong><\/p>\n 15:20 <\/b>Break<\/p>\n 15:40 Keynote #3: Herding wild cats: Performance and persistence in the Caracal deterministic database<\/strong>, Angela Demke Brown<\/span> (University of Toronto)<\/b><\/p>\n 16:40 Closing remarks<\/strong><\/p>\n 16:55<\/b>\u00a0– 19:00 <\/strong>Poster session and Reception (CS Taub building \u2013 hall)<\/strong>\u00a0<\/b><\/p>\nKeynote #02<\/h4>\n
Improving Cloud Security with Hardware Memory Capabilities<\/h2>\n<\/div>
Peter Pietzuch (Imperial College London)<\/strong><\/em><\/h3>\n
Keynote #03<\/h4>\n
Herding wild cats: Performance and persistence in the Caracal deterministic database<\/h2>\n<\/div>
Angela Demke Brown (University of <\/strong><\/em>Toronto<\/strong><\/em>)<\/strong><\/em><\/h3>\n
Full Program<\/h2>\n[\/vc_column][\/vc_row][vc_row tm_bgimagefixed=”” break_in_responsive=”991″ tm_zindex=”2″ full_width=”stretch_row” tm_responsive_css=”60233685|colbreak_no|||||||||colbreak_no|||||55px||25px||colbreak_no||||||||||colbreak_no|||||||||” css=”.vc_custom_1652169372450{padding-top: 111px !important;padding-bottom: 0px !important;}”][vc_column reduce_extra_padding=”991″ width=”1\/2″ tm_responsive_css=”22114509|colbreak_no|||||||||colbreak_no|||||||||colbreak_no||||||||||colbreak_no|||||||||” css=”.vc_custom_1626073647852{padding-right: 100px !important;}”][vc_column_text]<\/p>\n
Day 1: Monday, June 5<\/strong><\/h3>\n
\n
\n Peter-Jan Gootzen<\/span><\/strong>, Jonas Pfefferle and Radu Stoica, IBM Research Zurich;<\/em> Animesh Trivedi, VU Amsterdam<\/em><\/li>\n
\nAlex Merenstein<\/span><\/strong>, Stony Brook University;<\/em> Vasily Tarasov, IBM Research;<\/em> Ali Anwar, University of Minnesota;<\/em> Scott Guthridge, IBM Research;<\/em> Erez Zadok, Stony Brook University<\/em><\/li>\n
\n Hojin Park<\/span><\/strong>, Greg R. Ganger and George Amvrosiadis, Carnegie Mellon University<\/em><\/li>\n<\/ul>\n\n
\nXingsheng Zhao, Chen Zhong and Song Jiang<\/span><\/strong>. University of Texas at Arlington<\/em><\/li>\n
\n Shukai Han<\/span><\/strong>, Mi Zhang, Dejun Jiang and Jin Xiong, Institute of Computing Technology, Chinese Academy of Sciences<\/em><\/li>\n
\nSeungjin Lee<\/span><\/strong>, Chang-Gyu Lee and Donghyun Min, Sogang University;<\/em> Inhyuk Park and Woosuk Chung, SK hynix;<\/em> Anand Sivasubramaniam, Pennsylvania State University; Youngjae Kim, Sogang University<\/em><\/li>\n<\/ul>\n
\n<\/b><\/p>\nDay 2: Tuesday, June 6<\/strong><\/h3>\n
\n
\nInho Song<\/span><\/strong> and Myounghoon Oh, Dankook University;<\/em> Bryan S. Kim, Syracuse University;<\/em> Seehwan Yoo,\u00a0 Jaedong Lee and Jongmoo Choi, Dankook University<\/em><\/li>\n
\nZheng Gu, Jiangpeng Li, Yong Peng, Yang Liu and Tong Zhang<\/span><\/strong>, ScaleFlux<\/em><\/li>\n\n
\nLei Lei, Decai Pan<\/span><\/strong>\u00a0and Li Lin. Chongqing University;<\/em> Peng Ouyang, TsingMicro Co. Ltd.;<\/em> Xuelaing Du, Beijing Baidu Netcom Science Technology Co., Ltd<\/em>.; Dajiang Liu, Chongqing University<\/em><\/li>\n
\nErik Altman<\/span><\/strong>\u00a0and Benjamin Segal, IBM<\/em><\/li>\n
\nHeting Liu<\/span><\/strong> and Zhichao Li, ByteDance Inc.;<\/em> Cheng Tan, Northeastern University;<\/em> Rongqiu Yang, ByteDance Inc.;<\/em> Guohong Cao, Pennsylvania State University;<\/em> Zherui Liu and Chuanxiong Guo, Bytedance Inc.<\/em><\/li>\n<\/ul>\n\n
\nJun Lin Chen and Daniyal Liaqat, University of Toronto; <\/em>Moshe Gabel<\/span><\/strong>, York University \/ University of Toronto; <\/em>Eyal de Lara, University of Toronto<\/em><\/li>\n
\nLior Zeno,\u00a0Technion;<\/em>\u00a0Dan R. K. Ports, Jacob Nelson, and Daehyeok Kim,\u00a0Microsoft Research;<\/em>\u00a0Shir Landau Feibish,\u00a0The Open University of Israel;<\/em>\u00a0Idit Keidar, Arik Rinberg, Alon Rashelbach, Igor De-Paula, and Mark Silberstein<\/span><\/strong>,\u00a0Technion<\/em><\/li>\n
\nDima Kuznetsov<\/span><\/strong> and Adam Morrison. Tel Aviv University<\/em><\/li>\n
\nAlon Rashelbach<\/span><\/strong>, Ori Rottenstreich and Mark Silberstein, Technion<\/em><\/li>\n<\/ul>\nDay 3: Wednesday, June 7<\/strong><\/h3>\n