Automatically Tolerating And Correcting Memory Errors
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Applications written in unsafe languages like C and C++ are vulnerable to memory errors such as buffer overflows, dangling pointers, and reads of uninitialized data. These errors, which lead to program crashes, security vulnerabilities, and unpredictable behavior, are both difficult to avoid and costly to repair. This talk presents two systems that automatically harden unaltered C and C++ programs against heap-based memory errors. The first, DieHard, uses randomization and replication to make programs probabilistically resistant to a wide range of memory errors. Instead of crashing or running amok, DieHard lets programs run correctly in the face of memory errors with high probability. DieHard trades a modest increase in memory consumption (and optionally, the extra processing power of multicore CPUs) for dramatically increased reliability. While DieHard tolerates errors, our second system, Exterminator, automatically isolates and corrects them. Exterminator exploits randomization to pinpoint errors with high precision. From this information, Exterminator generates patches that fix these errors in current and subsequent executions. In addition, Exterminator enables collaborative bug correction by merging patches generated by multiple users.
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![Automatically Tolerating & Correcting Memory Errors Emery Berger University of Massachusetts Amherst joint work with Gene Novark (UMass Amherst), Ben Zorn (Microsoft Research) [PLDI 2006, PLDI 2007] TexPoint fonts used in EMF. Read the TexPoint manual before you delete this box.: A A A A A A A](https://image.slidesharecdn.com/automatically-tolerating-and-correcting-memory-errors2423/85/Automatically-Tolerating-And-Correcting-Memory-Errors-1-320.jpg)
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This document discusses machine learning on source code. It begins by defining machine learning on source code as applying machine learning where the input data is source code. It then discusses some of the challenges of applying machine learning to source code, including data retrieval and analysis. Finally, it provides examples of potential use cases like predicting the next token in code, learning to represent programs with graphs, and building tools to assist with code reviews.
New zealand bloom filter
Bloom filters provide a space-efficient probabilistic data structure for representing a set in order to support membership queries. They allow false positives but no false negatives. The structure uses k hash functions to map elements to bit positions in a bit array. Querying whether an element is in the set checks if the corresponding bit positions are all set to 1. Modern applications include distributed caching, peer-to-peer networks, routing, and measurement infrastructure where Bloom filters trade off exact representation for speed and space efficiency.
Os Vanrossum
Python 3000 (Python 3.0) is an upcoming major release that will break backwards compatibility to fix early design mistakes and issues. It introduces many changes like Unicode as the default string type, a reworked I/O library, print as a function, and removal of some old features like classic classes. The document provides details on the changes and recommends projects support both Python 2.6 and 3.0 during the transition period.
Finding similar items in high dimensional spaces locality sensitive hashing
This document discusses using locality sensitive hashing (LSH) to efficiently find similar items in high-dimensional spaces. It describes how LSH works by first representing items as sets of shingles/n-grams, then using minhashing to map these sets to compact signatures while preserving similarity. It explains that LSH further hashes the signatures into "bands" to generate candidate pairs that are likely similar and need direct comparison. The number of bands can be tuned to tradeoff between finding most similar pairs vs few dissimilar pairs.
Дмитрий Селиванов, OK.RU. Finding Similar Items in high-dimensional spaces: L...
Дмитрий рассказал о методе снижения размерности многомерных данных – Locality Sensitive Hashing. На примере задачи поиска похожих текстовых документов гости был подробно разобран алгоритм Minhash.
A Short Course in Data Stream Mining
Slides for a short course in data stream mining, showing classification, adaptive methods, clustering and frequent pattern methods.
Handling Exceptions In C & C++ [Part B] Ver 2
This document discusses exception handling in C++. It provides an overview of how compilers manage exceptional control flow and how functions are instrumented to handle exceptions. It discusses normal vs exceptional function call flows, and the items involved in stack frames like context, finalization, and unwinding. It also summarizes Meyers' guidelines for exception safety, including using destructors to prevent leaks, handling exceptions in constructors, and preventing exceptions from leaving destructors.
Exploiting Multicore CPUs Now: Scalability and Reliability for Off-the-shelf ...
Multiple core CPUs are here. Conventional wisdom holds that, to take best advantage of these processors, we now need to rewrite sequential applications to make them multithreaded. Because of the difficulty of programming correct and efficient multithreaded applications (e.g., race conditions, deadlocks, and scalability bottlenecks), this is a major challenge.
This talk presents two alternative approaches that bring the power of multiple cores to today's software. The first approach focuses on building highly-concurrent client-server applications from legacy code. I present a system called Flux that allows users to take unmodified off-the-shelf *sequential* C and C++ code and build concurrent applications. The Flux compiler combines the Flux program and the sequential code to generate a deadlock-free, high-concurrency server. Flux also generates discrete event simulators that accurately predict actual server performance under load. While the Flux language was initially targeted at servers, we have found it to be a useful abstraction for sensor networks, and I will briefly talk about our use of an energy-aware variant of Flux in a deployment on the backs of endangered turtles. The second approach uses the extra processing power of multicore CPUs to make legacy C/C++ applications more reliable. I present a system called DieHard that uses randomization and replication to transparently harden programs against a wide range of errors, including buffer overflows and dangling pointers. Instead of crashing or running amok, DieHard lets programs continue to run correctly in the face of memory errors with high probability. This is joint work with Brendan Burns, Kevin Grimaldi, Alex Kostadinov, Jacob Sorber, and Mark Corner (University of Massachusetts Amherst), and Ben Zorn (Microsoft Research).
Java Garbage Collection, Monitoring, and Tuning
The document discusses Java garbage collection. It explains that garbage collection automatically reclaims memory from objects that are no longer reachable to avoid memory leaks. It describes different garbage collection algorithms and strategies like generational and incremental garbage collection. It also discusses best practices and myths around memory management in Java.
Polymer Brush Data Processor
An automated C++ program was created to process atomic force microscopy (AFM) image data to reduce manual processing time from 24 hours to less than 2 hours. The program analyzes AFM image cross-sections by automatically extracting height, width, and area values with 99.5% precision compared to manual processing. It prompts the user for input, imports AFM data, analyzes slopes and derivatives to identify cross-section boundaries, then calculates metrics like height, width, and area which it outputs to an Excel file.
Ajax and JavaScript Bootcamp
A great intro to JavaScript. Covers all the basics you need to get up and running with Ajax development. http://www.enterpriseajax.com
Internet of Things Data Science
The document discusses data stream classification and algorithms for handling data streams. It begins with an introduction to data stream characteristics and challenges. It then discusses approximation algorithms for data streams, including maintaining statistics over sliding windows. Classification algorithms for data streams discussed include Naive Bayes classifiers, perceptrons, and Hoeffding trees, which are decision trees adapted for data streams using the Hoeffding bound inequality to determine the optimal split attribute.
.NET Fest 2018. Maarten Balliauw. Let’s refresh our memory! Memory management...
The .NET Garbage Collector (GC) is really cool. It helps providing our applications with virtually unlimited memory, so we can focus on writing code instead of manually freeing up memory. But how does .NET manage that memory? What are hidden allocations? Are strings evil? It still matters to understand when and where memory is allocated. In this talk, we’ll go over the base concepts of .NET memory management and explore how .NET helps us and how we can help .NET – making our apps better. Expect profiling, Intermediate Language (IL), ClrMD and more!
1.Buffer Overflows
Course : Introduction to Big Data with Apache Spark : http://ouo.io/Mqc8L5
Course : Spark Fundamentals I : http://ouo.io/eiuoV
Course : Functional Programming Principles in Scala : http://ouo.io/rh4vv
DotNetFest - Let’s refresh our memory! Memory management in .NET
The .NET Garbage Collector (GC) is really cool. It helps providing our applications with virtually unlimited memory, so we can focus on writing code instead of manually freeing up memory. But how does .NET manage that memory? What are hidden allocations? Are strings evil? It still matters to understand when and where memory is allocated. In this talk, we’ll go over the base concepts of .NET memory management and explore how .NET helps us and how we can help .NET – making our apps better. Expect profiling, Intermediate Language (IL), ClrMD and more!
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Finding similar items in high dimensional spaces locality sensitive hashing
Finding similar items in high dimensional spaces locality sensitive hashing
Дмитрий Селиванов, OK.RU. Finding Similar Items in high-dimensional spaces: L...
Дмитрий Селиванов, OK.RU. Finding Similar Items in high-dimensional spaces: L...
Exploiting Multicore CPUs Now: Scalability and Reliability for Off-the-shelf ...
Exploiting Multicore CPUs Now: Scalability and Reliability for Off-the-shelf ...
.NET Fest 2018. Maarten Balliauw. Let’s refresh our memory! Memory management...
.NET Fest 2018. Maarten Balliauw. Let’s refresh our memory! Memory management...
DotNetFest - Let’s refresh our memory! Memory management in .NET
DotNetFest - Let’s refresh our memory! Memory management in .NET
More from Emery Berger
Doppio: Breaking the Browser Language Barrier
Web browsers have become a de facto universal operating system, and JavaScript its instruction set. Unfortunately, running other languages in the browser is not generally possible. Translation to JavaScript is not enough because browsers are a hostile environment for other languages. Previous approaches are either non-portable or require extensive modifications for programs to work in a browser.
This talk presents Doppio, a JavaScript-based runtime system that makes it possible to run unaltered applications written in general- purpose languages directly inside the browser. Doppio provides a wide range of runtime services, including a file system that enables local and external (cloud-based) storage, an unmanaged heap, sockets, blocking I/O, and multiple threads. We demonstrate Doppio's usefulness with two case studies: we extend Emscripten with Doppio, letting it run an unmodified C++ application in the browser with full functionality, and present DoppioJVM, an interpreter that runs unmodified JVM programs directly in the browser. While substantially slower than a native JVM, DoppioJVM makes it feasible to directly reuse existing, non compute-intensive code.
Dthreads: Efficient Deterministic Multithreading
Dthreads is an efficient deterministic multithreading system for unmodified C/C++ applications that replaces the pthreads library. Dthreads enforces determinism in the face of data races and deadlocks. It is easy to use: just link your program with -ldthread instead of -lpthread.
Dthreads can be downloaded from its source code repo on GitHub (https://github.com/plasma-umass/dthreads). A technical paper describing Dthreads appeared at SOSP 2012 (https://github.com/plasma-umass/dthreads/blob/master/doc/dthreads-sosp11.pdf?raw=true).
Multithreaded programming is notoriously difficult to get right. A key problem is non-determinism, which complicates debugging, testing, and reproducing errors. One way to simplify multithreaded programming is to enforce deterministic execution, but current deterministic systems for C/C++ are incomplete or impractical. These systems require program modification, do not ensure determinism in the presence of data races, do not work with general-purpose multithreaded programs, or run up to 8.4× slower than pthreads.
This talk presents Dthreads, an efficient deterministic multithreading system for unmodified C/C++ applications that replaces the pthreads library. Dthreads enforces determinism in the face of data races and deadlocks. Dthreads works by exploding multithreaded applications into multiple processes, with private, copy-on-write mappings to shared memory. It uses standard virtual memory protection to track writes, and deterministically orders updates by each thread. By separating updates from different threads, Dthreads has the additional benefit of eliminating false sharing. Experimental results show that Dthreads substantially outperforms a state-of-the-art deterministic runtime system, and for a majority of the benchmarks we evaluated, matches and occasionally exceeds the performance of pthreads.
Programming with People
The document describes a system called AutoMan that integrates human computation via Amazon Mechanical Turk (MTurk) into programming. AutoMan allows programmers to write functions that are implemented by having MTurk workers complete small tasks. It addresses challenges like ensuring quality work from workers and preventing gaming of the system. AutoMan manages pricing, timing of tasks, and number of workers to balance cost, speed and accuracy of results for user-defined functions.
Stabilizer: Statistically Sound Performance Evaluation
The document describes how memory layout affects program performance evaluation and how STABILIZER addresses this issue. STABILIZER eliminates the effect of memory layout on performance so that the true effect of a code change can be measured in isolation, enabling statistically sound performance evaluation. It discusses how traditional methods of repeated runs and error bars are not sufficient and presents case studies showing how STABILIZER enables evaluating the performance of LLVM optimizations accurately.
DieHarder (CCS 2010, WOOT 2011)
Heap-based attacks depend on a combination of memory management errors and an exploitable memory allocator. Many allocators include ad hoc countermeasures against particular exploits, but their effectiveness against future exploits has been uncertain.
This paper presents the first formal treatment of the impact of allocator design on security. It analyzes a range of widely-deployed memory allocators, including those used by Windows, Linux, FreeBSD, and OpenBSD, and shows that they remain vulnerable to attack. It then presents DieHarder, a new allocator whose design was guided by this analysis. DieHarder provides the highest degree of security from heap-based attacks of any practical allocator of which we are aware, while imposing modest performance overhead. In particular, the Firefox web browser runs as fast with DieHarder as with the Linux allocator.
Operating Systems - Advanced File Systems
This document discusses distributed file systems and some of their key design considerations. It covers issues like naming and transparency in distributed file systems, different approaches to naming like absolute vs relative names, caching strategies like write-back vs write-through, and consistency models. It also provides examples of different distributed file systems like NFS, AFS, and Sprite and discusses some of their approaches.
Operating Systems - File Systems
This document discusses operating systems and file systems. It covers topics such as hierarchical directory structures, files, directories, metadata, access control, and different types of files in Unix systems like regular files, devices, pipes and the proc filesystem. Examples are given of how to view file metadata using ls and change access permissions using chmod. The document is a set of lecture slides on these fundamental file system concepts.
Operating Systems - Networks
The document discusses computer networks and operating systems. It covers topics like local and wide area networks, protocols, packet formats, sockets, client-server communication, and network topologies. Specifically, it describes how data is broken into packets and transmitted over networks using protocols like TCP and UDP. It also discusses common network topologies like bus, point-to-point, and tree structures.
Operating Systems - Queuing Systems
The document discusses queuing systems and networks. It describes how queuing networks can model concurrent systems with nodes that include queues and servers. Key concepts discussed include arrival and service rates, stable systems where arrival equals departure rates, and Little's Law relating queue length, arrival rate, and wait time. The document also introduces Flux, a programming language for building high-performance concurrent servers by combining sequential components with defined flows and atomicity.
Operating Systems - Distributed Parallel Computing
The document discusses distributed parallel programming and message passing. It begins with an introduction to distributed memory machines and message passing as a programming model. It then covers the Message Passing Interface (MPI) library for message passing and provides an example MPI program that prints "Hello world" from multiple processes. The document also discusses sending and receiving messages directly between processes.
Operating Systems - Concurrency
The document discusses concurrency patterns for operating systems and presents examples using a web server. It introduces the thread pool and producer-consumer patterns for improving concurrency and hiding latency from I/O. The producer-consumer pattern is explored in more detail for a web server application with examples of using multiple queues and threads to parallelize work.
Operating Systems - Advanced Synchronization
This document discusses synchronization in operating systems and computer science. It covers topics like locks, mutexes, semaphores, and condition variables. Locks are used for mutual exclusion to ensure only one thread accesses a critical section at a time. Semaphores generalize locks and can be used to coordinate threads and signal events. Readers-writer locks allow multiple reader threads but only one writer thread for optimization. Common synchronization issues like deadlocks, priority inversion, and failures to unlock are also addressed.
Operating Systems - Synchronization
This document discusses synchronization in operating systems and concurrent programming. It introduces the concept of critical sections and mutual exclusion locks that allow only one thread to access shared data at a time. It presents solutions to the "too much milk" problem using notes and waiting to ensure only one thread buys milk at a time. The document then discusses implementing locks using disabling interrupts as well as higher-level synchronization primitives like semaphores and monitors that make concurrent programming easier.
Processes and Threads
This document summarizes a lecture on processes and threads. It discusses the key differences between processes and threads, including that processes have separate address spaces while threads share an address space. It covers process and thread APIs, examples of using processes and threads, interprocess communication techniques like pipes and sockets, and considerations for when to use processes versus threads, such as that threads have lower overhead but processes are more robust.
Virtual Memory and Paging
This document summarizes a lecture on virtual memory and paging given by Emery Berger at the University of Massachusetts Amherst. It discusses how virtual memory uses an indirection layer between physical and virtual addresses via a memory management unit (MMU) and page table. This indirection allows for isolation between processes, simplifies memory management, and enables optimizations like sharing and swapping of memory pages to disk. It also describes how translation lookaside buffers (TLBs) cache page translations for faster address translation and outlines the life cycle of a memory page from allocation to eviction and replacement.
Operating Systems - Virtual Memory
This document summarizes a lecture on virtual memory. It discusses how virtual memory uses page tables to map virtual addresses to physical addresses, allowing processes to access more memory than is physically available. It describes demand paging, where pages are loaded on demand from disk, and the translation lookaside buffer (TLB) that caches translations to improve performance. Common page replacement algorithms like least recently used (LRU) and first-in first-out (FIFO) are also summarized.
MC2: High-Performance Garbage Collection for Memory-Constrained Environments
MC2 is an incremental, space-efficient garbage collector that has high throughput and low pause times. This talk was presented at OOPSLA 2004.
Vam: A Locality-Improving Dynamic Memory Allocator
Presents Vam, a memory allocator that improves cache-level and virtual memory locality. Vam is distributed with Heap Layers (www.heaplayers.org)..
Quantifying the Performance of Garbage Collection vs. Explicit Memory Management
This talk answers an age-old question: is garbage collection faster/slower/the same speed as malloc/free? We introduce oracular memory management, an approach that lets us measure unaltered Java programs as if they used malloc and free. The result: a good GC can match the performance of a good allocator, but it takes 5X more space. If physical memory is tight, however, conventional garbage collectors suffer an order-of-magnitude performance penalty.
Garbage Collection without Paging
Introduces bookmarking collection, a GC algorithm that works with the virtual memory manager to eliminate paging. Just before memory is paged out, the collector "bookmarks" the targets of pointers from the pages. Using these bookmarks, BC can perform full garbage collections without loading the pages back from disk. By performing in-memory garbage collections, BC can speed up Java programs by orders of magnitude (up to 41X).
More from Emery Berger (20)
Stabilizer: Statistically Sound Performance Evaluation
Stabilizer: Statistically Sound Performance Evaluation
Operating Systems - Distributed Parallel Computing
Operating Systems - Distributed Parallel Computing
MC2: High-Performance Garbage Collection for Memory-Constrained Environments
MC2: High-Performance Garbage Collection for Memory-Constrained Environments
Vam: A Locality-Improving Dynamic Memory Allocator
Vam: A Locality-Improving Dynamic Memory Allocator
Quantifying the Performance of Garbage Collection vs. Explicit Memory Management
Quantifying the Performance of Garbage Collection vs. Explicit Memory Management
Recently uploaded
5th LF Energy Power Grid Model Meet-up Slides
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
Dandelion Hashtable: beyond billion requests per second on a commodity server
This slide deck presents DLHT, a concurrent in-memory hashtable. Despite efforts to optimize hashtables, that go as far as sacrificing core functionality, state-of-the-art designs still incur multiple memory accesses per request and block request processing in three cases. First, most hashtables block while waiting for data to be retrieved from memory. Second, open-addressing designs, which represent the current state-of-the-art, either cannot free index slots on deletes or must block all requests to do so. Third, index resizes block every request until all objects are copied to the new index. Defying folklore wisdom, DLHT forgoes open-addressing and adopts a fully-featured and memory-aware closed-addressing design based on bounded cache-line-chaining. This design offers lock-free index operations and deletes that free slots instantly, (2) completes most requests with a single memory access, (3) utilizes software prefetching to hide memory latencies, and (4) employs a novel non-blocking and parallel resizing. In a commodity server and a memory-resident workload, DLHT surpasses 1.6B requests per second and provides 3.5x (12x) the throughput of the state-of-the-art closed-addressing (open-addressing) resizable hashtable on Gets (Deletes).
Main news related to the CCS TSI 2023 (2023/1695)
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
Skybuffer SAM4U tool for SAP license adoption
Manage and optimize your license adoption and consumption with SAM4U, an SAP free customer software asset management tool.
SAM4U, an SAP complimentary software asset management tool for customers, delivers a detailed and well-structured overview of license inventory and usage with a user-friendly interface. We offer a hosted, cost-effective, and performance-optimized SAM4U setup in the Skybuffer Cloud environment. You retain ownership of the system and data, while we manage the ABAP 7.58 infrastructure, ensuring fixed Total Cost of Ownership (TCO) and exceptional services through the SAP Fiori interface.
Programming Foundation Models with DSPy - Meetup Slides
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
Digital Banking in the Cloud: How Citizens Bank Unlocked Their Mainframe
Inconsistent user experience and siloed data, high costs, and changing customer expectations – Citizens Bank was experiencing these challenges while it was attempting to deliver a superior digital banking experience for its clients. Its core banking applications run on the mainframe and Citizens was using legacy utilities to get the critical mainframe data to feed customer-facing channels, like call centers, web, and mobile. Ultimately, this led to higher operating costs (MIPS), delayed response times, and longer time to market.
Ever-changing customer expectations demand more modern digital experiences, and the bank needed to find a solution that could provide real-time data to its customer channels with low latency and operating costs. Join this session to learn how Citizens is leveraging Precisely to replicate mainframe data to its customer channels and deliver on their “modern digital bank” experiences.
Best 20 SEO Techniques To Improve Website Visibility In SERP
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
TrustArc Webinar - 2024 Global Privacy Survey
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
Generating privacy-protected synthetic data using Secludy and Milvus
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
“How Axelera AI Uses Digital Compute-in-memory to Deliver Fast and Energy-eff...
“How Axelera AI Uses Digital Compute-in-memory to Deliver Fast and Energy-eff...Edge AI and Vision Alliance
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/how-axelera-ai-uses-digital-compute-in-memory-to-deliver-fast-and-energy-efficient-computer-vision-a-presentation-from-axelera-ai/
Bram Verhoef, Head of Machine Learning at Axelera AI, presents the “How Axelera AI Uses Digital Compute-in-memory to Deliver Fast and Energy-efficient Computer Vision” tutorial at the May 2024 Embedded Vision Summit.
As artificial intelligence inference transitions from cloud environments to edge locations, computer vision applications achieve heightened responsiveness, reliability and privacy. This migration, however, introduces the challenge of operating within the stringent confines of resource constraints typical at the edge, including small form factors, low energy budgets and diminished memory and computational capacities. Axelera AI addresses these challenges through an innovative approach of performing digital computations within memory itself. This technique facilitates the realization of high-performance, energy-efficient and cost-effective computer vision capabilities at the thin and thick edge, extending the frontier of what is achievable with current technologies.
In this presentation, Verhoef unveils his company’s pioneering chip technology and demonstrates its capacity to deliver exceptional frames-per-second performance across a range of standard computer vision networks typical of applications in security, surveillance and the industrial sector. This shows that advanced computer vision can be accessible and efficient, even at the very edge of our technological ecosystem.Driving Business Innovation: Latest Generative AI Advancements & Success Story
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Apps Break Data
How information systems are built or acquired puts information, which is what they should be about, in a secondary place. Our language adapted accordingly, and we no longer talk about information systems but applications. Applications evolved in a way to break data into diverse fragments, tightly coupled with applications and expensive to integrate. The result is technical debt, which is re-paid by taking even bigger "loans", resulting in an ever-increasing technical debt. Software engineering and procurement practices work in sync with market forces to maintain this trend. This talk demonstrates how natural this situation is. The question is: can something be done to reverse the trend?
FREE A4 Cyber Security Awareness Posters-Social Engineering part 3
Free A4 downloadable and printable Cyber Security, Social Engineering Safety and security Training Posters . Promote security awareness in the home or workplace. Lock them Out From training providers datahops.com
What is an RPA CoE? Session 1 – CoE Vision
In the first session, we will review the organization's vision and how this has an impact on the COE Structure.
Topics covered:
• The role of a steering committee
• How do the organization’s priorities determine CoE Structure?
Speaker:
Chris Bolin, Senior Intelligent Automation Architect Anika Systems
Taking AI to the Next Level in Manufacturing.pdf
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectors
Join us to learn how UiPath Apps can directly and easily interact with prebuilt connectors via Integration Service--including Salesforce, ServiceNow, Open GenAI, and more.
The best part is you can achieve this without building a custom workflow! Say goodbye to the hassle of using separate automations to call APIs. By seamlessly integrating within App Studio, you can now easily streamline your workflow, while gaining direct access to our Connector Catalog of popular applications.
We’ll discuss and demo the benefits of UiPath Apps and connectors including:
Creating a compelling user experience for any software, without the limitations of APIs.
Accelerating the app creation process, saving time and effort
Enjoying high-performance CRUD (create, read, update, delete) operations, for
seamless data management.
Speakers:
Russell Alfeche, Technology Leader, RPA at qBotic and UiPath MVP
Charlie Greenberg, host
Choosing The Best AWS Service For Your Website + API.pptx
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
Recently uploaded (20)
Dandelion Hashtable: beyond billion requests per second on a commodity server
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- 1. Automatically Tolerating & Correcting Memory Errors Emery Berger University of Massachusetts Amherst joint work with Gene Novark (UMass Amherst), Ben Zorn (Microsoft Research) [PLDI 2006, PLDI 2007] TexPoint fonts used in EMF. Read the TexPoint manual before you delete this box.: A A A A A A A
- 29. Exterminator: Automatically Correcting Memory Errors with High Probability
- 55. Exterminator Runtime Overhead 25%
- 59. The End www.diehard-software.org www.cs.umass.edu/~emery