PPT-Shreds: Fine-grained Execution Units with Private Memory

Author : sherrill-nordquist | Published Date : 2018-03-17

Landon Cox March 3 2017 Parts of a process Threads Sequences of executing instructions Active do things Address space Data the process uses as it runs Passive

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Shreds: Fine-grained Execution Units with Private Memory: Transcript

Landon Cox March 3 2017 Parts of a process Threads Sequences of executing instructions Active do things Address space Data the process uses as it runs Passive acted upon by . Avg Access Time 2 Tokens Number of Controllers Average Access Time clock cyles brPage 16br Number of Tokens vs Avg Access Time 9 Controllers Number of Tokens Average Access Time clock cycles brPage 17br brPage 18br Register-Aware Application . Mapping . on Coarse-Grained Reconfigurable Architectures. Mahdi . Hamzeh. , . Aviral. . Shrivastava. , and . Sarma. . Vrudhula. School of Computing, Informatics, and Decision Systems Engineering. Kevin Wallace, CSE504. 2010-04-28. 2. Problem. Attacker-facing code must be written to guard against all possible inputs. There are many execution paths; not a single one should lead to a vulnerability. Todd Frederick. Vulnerabilities are everywhere…. 2. Binary Concolic Execution. rtm. Robert Morris. An exploit. 3. Binary Concolic Execution. DD8F2F736800DD8F2F62696ED05E5ADD00DD00DD5ADD03D05E5CBC3B. Liwen. Sun, Michael J. Franklin, Sanjay Krishnan, Reynold S. . Xin†. UC . Berkeley and †. Databricks. Inc. .. VLDB 2014. March 17, 2015. Heymo. Kou. Introduction. Overview. Workload Analysis. The Partitioning Problem. Xen. Bhanu Vattikonda. with . Sambit. Das and . Hovav. . Shacham. 2. Motivation . Project goals. Goals of the paper. Discussion . Future work. Motivation. 3. Recent research efforts have shown that covert channel attacks are possible in the cloud using fine grained timers . Andréia Marini . Adviser: Alessandro L. . Koerich. Postgraduate . Program in Computer Science (. PPGIa. ) . Pontifical . Catholic University of . Paraná (PUCPR). Outline. Motivation. The . Challenge. Man Cao. Jake . Roemer. Aritra. . Sengupta. Michael D. Bond. 1. Parallel Programming is Hard. 2. Parallel Programming is Hard. Shared-memory. 3. Main Memory. CPU. Cache. CPU. Cache. CPU. Cache. CPU. Man Cao. Jake . Roemer. Aritra. . Sengupta. Michael D. Bond. 1. Parallel Programming is Hard. 2. Parallel Programming is Hard. Shared-memory. 3. Main Memory. CPU. Cache. CPU. Cache. CPU. Cache. CPU. . NFs. . for. . Flexiable. . per-flow. . Customization. Wei Zhang, Jinho Hwang, Shriram Rajagopal, k.k. . ramakrishnan. and . timothy. . wood. – conext 2016. From: Class Wide Monolithic NFs . Landscape Ecology. Representation of scale-dependent landscape . structures responded to by a wren and a hawk.. Carolina. Wren. Red-. tailed. Hawk. Hostetler and Holling 2000. r vs. k selection life history strategies. AlZnMg-Zr . alloy. Nguyen Q. . Chinh. , . Jenő . Gubicza, . János. L. . Lábár. , . Zsolt. Kovács. , . János. . Lendvai. , . Elena V. . Bobruk, . Maxim Yu. . Murashkin . and Ruslan Z. . Valiev. Joel Kamdem Teto. z. Introduction. Fine-grained Multithreading . The ability of a single core to handle multiple thread by:. Providing a register for each thread. Dividing the pipeline bandwidth into N part . Abaz . Kryemadhi. , Andreas . Mastronikolis, . Konstantin Zioutas. 17. th. . Patras. workshop on . Axions. , WIMPS, and WISPS, . Aug. 8-12, 2022, Mainz Germany. 1. Profited from Mark Vogelsberger.

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