Ecosystem Alliance Manager Michael Ocampo talks about the CXL industry's effort to break through the memory wall, memory bound use cases, CXL for modular shared infrastructure, and critical CXL collaboration that's happening now.
Torry Steed, Sr. Product Marketing Manager at SMART Modular, provides an overview of CXL PCIe Add-in Cards (AICs) and memory modules that can be used to expand capacity in servers or in external memory pooling systems.
Q1 Memory Fabric Forum: Using CXL with AI Applications - Steve Scargall.pptxMemory Fabric Forum
MemVerge product manager and software architect Steve Scargall discusses key factors related to the use of CXL with AI apps including, memory expansion form factors, latency and bandwidth memory placement strategies, RDBMS investigation and results, vector database investigation, and results understanding your application behavior.
Q1 Memory Fabric Forum: Memory expansion with CXL-Ready Systems and DevicesMemory Fabric Forum
Ravi Gummaluri, Director, CXL System Architecture at Micron describes use cases for memory expansion with tiered DRAM and CXL memory, along with performance data.
Q1 Memory Fabric Forum: Intel Enabling Compute Express Link (CXL)Memory Fabric Forum
- Memory intensive workloads are dominating computing and increasing memory capacity just with CPU-attached DRAM is getting expensive.
- CXL allows augmenting system memory footprint at lower cost by running over existing PCIe links to add memory outside of the CPU package.
- Intel Xeon roadmap fully supports CXL starting with 5th Gen Xeons, and Intel CPUs offer unique hardware-based tiering modes between native DRAM and CXL memory without depending on the operating system.
- CXL has full industry support as the standard for coherent input/output.
MemVerge Field CTO Yong Tian shows what memory expansion costs with an analysis of various server configurations with up to 8TB of tiered DRAM and CXL memory.
Q1 Memory Fabric Forum: Memory Processor Interface 2023, Focus on CXLMemory Fabric Forum
Thibault Grossi, Sr. Technology & Market Analyst, shares excerpts from the recently published report, Memory Processor Interface, Focus on CXL. The reports provides a taxonomy of CXL market segments and revenue forecasts through 2028.
Ecosystem Alliance Manager Michael Ocampo talks about the CXL industry's effort to break through the memory wall, memory bound use cases, CXL for modular shared infrastructure, and critical CXL collaboration that's happening now.
Torry Steed, Sr. Product Marketing Manager at SMART Modular, provides an overview of CXL PCIe Add-in Cards (AICs) and memory modules that can be used to expand capacity in servers or in external memory pooling systems.
Q1 Memory Fabric Forum: Using CXL with AI Applications - Steve Scargall.pptxMemory Fabric Forum
MemVerge product manager and software architect Steve Scargall discusses key factors related to the use of CXL with AI apps including, memory expansion form factors, latency and bandwidth memory placement strategies, RDBMS investigation and results, vector database investigation, and results understanding your application behavior.
Q1 Memory Fabric Forum: Memory expansion with CXL-Ready Systems and DevicesMemory Fabric Forum
Ravi Gummaluri, Director, CXL System Architecture at Micron describes use cases for memory expansion with tiered DRAM and CXL memory, along with performance data.
Q1 Memory Fabric Forum: Intel Enabling Compute Express Link (CXL)Memory Fabric Forum
- Memory intensive workloads are dominating computing and increasing memory capacity just with CPU-attached DRAM is getting expensive.
- CXL allows augmenting system memory footprint at lower cost by running over existing PCIe links to add memory outside of the CPU package.
- Intel Xeon roadmap fully supports CXL starting with 5th Gen Xeons, and Intel CPUs offer unique hardware-based tiering modes between native DRAM and CXL memory without depending on the operating system.
- CXL has full industry support as the standard for coherent input/output.
MemVerge Field CTO Yong Tian shows what memory expansion costs with an analysis of various server configurations with up to 8TB of tiered DRAM and CXL memory.
Q1 Memory Fabric Forum: Memory Processor Interface 2023, Focus on CXLMemory Fabric Forum
Thibault Grossi, Sr. Technology & Market Analyst, shares excerpts from the recently published report, Memory Processor Interface, Focus on CXL. The reports provides a taxonomy of CXL market segments and revenue forecasts through 2028.
In the CXL Forum Theater at SC23 hosted by MemVerge, Samsung described their the architecture and use cases of their hybrid drive that includes DRAM and Flash memory
CXL Memory Expansion, Pooling, Sharing, FAM Enablement, and SwitchingMemory Fabric Forum
The document discusses CXL, a new open standard protocol for efficient CPU and memory connectivity. CXL allows for memory disaggregation and pooling across devices by enabling high-bandwidth, low-latency connections between CPUs, GPUs, accelerators, and memory. This helps address the growing CPU-memory bottleneck by allowing expansion of memory capacity beyond what can physically connect to the CPU. CXL also enables memory tiering by providing different performance and cost options for "near" directly attached memory versus "far" switched or fabric attached memory.
Arm: Enabling CXL devices within the Data Center with Arm SolutionsMemory Fabric Forum
During the CXL Forum at OCP Summit, Arm Director of Segment Marketing Parag Beeraka provides and overview of the Arm portfolio of CXL products for the Data Center
Torry Steed, Sr. Staff Product Manager at SMART Modular, covers the changing shape of memory leading to new categories of CXL form factors. He dives deeper to address EDSFF and AIC variations, mechanical sizes, installation locations, capacity considerations, and power ratings.
The document summarizes the architecture of the Argonne Cray XC40 KNL system called Theta. Key points include:
- Theta has 3,624 nodes with Intel Xeon Phi processors totaling 231,936 cores and 736 TB of memory.
- The Xeon Phi processors are Knights Landing chips running at 1.3GHz with 64 cores each and support the new AVX-512 instruction set.
- The system provides 10 PF of peak performance and uses Cray's high-speed Aries interconnect in a dragonfly topology.
- Benchmark results show strong floating point and memory bandwidth performance from the Knights Landing processors.
1) DDR memory technology enables memory subsystems to transfer data at twice the frequency of single data rate memory by transferring data on both the rising and falling edges of the clock. This improves performance but also makes the design and debugging more challenging due to reduced timing margins.
2) Debugging DDR memory modules requires examining components like the PLL to ensure proper clock generation and alignment, termination resistors to optimize timing, and registers to confirm signals are latched within specifications. Tuning elements like feedback capacitors and resistors can help optimize timing.
3) Testing tools are needed to thoroughly evaluate DDR memory, including memory testers, stress tests, and equipment to measure clock signals on DIMMs independently of a system
Supermicro Servers with Micron DDR5 & SSDs: Accelerating Real World WorkloadsRebekah Rodriguez
This document provides an overview of Supermicro's comprehensive server portfolio, including their rackmount, cloud, and mainstream server solutions. It highlights several multi-node server platforms like BigTwin, FatTwin, and GrandTwin. The document also mentions Supermicro will have many options for the upcoming 4th generation AMD EPYC 'Genoa' platform with support for up to 96 cores, 128 PCIe lanes, and DDR5 memory at up to 6TB capacity. In summary, the document outlines Supermicro's server product lines and upcoming support for the high-end 4th generation AMD EPYC processors.
Memory_Unit Cache Main Virtual AssociativeRNShukla7
The document discusses different types of computer memory organization including memory hierarchy, main memory, auxiliary memory, associative memory, cache memory, and virtual memory. It provides details on RAM and ROM chips used in main memory and how they are connected to the CPU through address and data buses. It also describes different memory mapping techniques used in cache memory including direct mapping, set-associative mapping, and associative mapping.
Internet of Things (IoT) data frequently has a location and time component. Getting value out of this "geotemporal" data can be tricky. We'll explore when and how to leverage Cassandra, DSE Search and DSE Analytics to surface meaningful information from your geotemporal data.
CXL is enabling new memory architectures by connecting CPUs and GPUs to shared memory pools. Early CXL 1.1 focused on memory expansion by connecting processors to DRAM modules. CXL 2.0 allowed for small memory pools accessible by a few servers. CXL 3.0 supports larger shared memory fabrics by connecting thousands of nodes and enabling true shared memory regions accessible coherently by multiple hosts and accelerators. However, shared memory fabrics using CXL 3.0 may experience greater latency variability and congestion compared to single-host or small memory pooling configurations.
DataStax: Extreme Cassandra Optimization: The SequelDataStax Academy
Al has been using Cassandra since version 0.6 and has spent the last few months doing little else but tune Cassandra clusters. In this talk, Al will show how to tune Cassandra for efficient operation using multiple views into system metrics, including OS stats, GC logs, JMX, and cassandra-stress.
Implementation of Dense Storage Utilizing HDDs with SSDs and PCIe Flash Acc...Red_Hat_Storage
At Red Hat Storage Day New York on 1/19/16, Red Hat partner Seagate presented on how to implement dense storage using HDDs with SSDs and PCIe flash accelerator cards.
During the CXL Forum at OCP Global Summit, MemVerge CEO Charles Fan presented accomplishments of the CXL industry since 2019, the development of concept cars occurring today, and his predictions for the future of CXL
Ceph Day Shanghai - SSD/NVM Technology Boosting Ceph Performance Ceph Community
This document discusses using SSDs and emerging non-volatile memory technologies like 3D XPoint to boost performance of Ceph storage clusters. It outlines how SSDs can be used as journals and caches to significantly increase throughput and reduce latency compared to HDD-only clusters. A case study from Yahoo showed that using Intel NVMe SSDs with caching software delivered over 2x throughput and half the latency with only 5% of data cached. Future technologies like 3D NAND and 3D XPoint will allow building higher performance, higher capacity SSDs that could extend the use of Ceph.
This document discusses memory design considerations for system-on-chip and board-based systems. It begins by explaining that memory system performance largely depends on the memory placement (on-die or off-die), access time, and bandwidth. It then provides an overview of different memory technologies that can be used for on-chip and external memory, such as SRAM, DRAM, flash memory, and discusses their characteristics. The document emphasizes that on-die memory allows faster access times compared to off-die memory, and discusses cache memory design approaches to compensate for longer off-die memory access times.
Q1 Memory Fabric Forum: ZeroPoint. Remove the waste. Release the power.Memory Fabric Forum
Nilesh Shah provide an overview of the ZeroPoint portable, hardware IP portfolio for lossless memory compression and compaction. The IP boosts memory capacity 2-4x, bandwidth and performance/watt by 50%, and is 1,000x faster than competitors.
In the CXL Forum Theater at SC23 hosted by MemVerge, Samsung described their the architecture and use cases of their hybrid drive that includes DRAM and Flash memory
CXL Memory Expansion, Pooling, Sharing, FAM Enablement, and SwitchingMemory Fabric Forum
The document discusses CXL, a new open standard protocol for efficient CPU and memory connectivity. CXL allows for memory disaggregation and pooling across devices by enabling high-bandwidth, low-latency connections between CPUs, GPUs, accelerators, and memory. This helps address the growing CPU-memory bottleneck by allowing expansion of memory capacity beyond what can physically connect to the CPU. CXL also enables memory tiering by providing different performance and cost options for "near" directly attached memory versus "far" switched or fabric attached memory.
Arm: Enabling CXL devices within the Data Center with Arm SolutionsMemory Fabric Forum
During the CXL Forum at OCP Summit, Arm Director of Segment Marketing Parag Beeraka provides and overview of the Arm portfolio of CXL products for the Data Center
Torry Steed, Sr. Staff Product Manager at SMART Modular, covers the changing shape of memory leading to new categories of CXL form factors. He dives deeper to address EDSFF and AIC variations, mechanical sizes, installation locations, capacity considerations, and power ratings.
The document summarizes the architecture of the Argonne Cray XC40 KNL system called Theta. Key points include:
- Theta has 3,624 nodes with Intel Xeon Phi processors totaling 231,936 cores and 736 TB of memory.
- The Xeon Phi processors are Knights Landing chips running at 1.3GHz with 64 cores each and support the new AVX-512 instruction set.
- The system provides 10 PF of peak performance and uses Cray's high-speed Aries interconnect in a dragonfly topology.
- Benchmark results show strong floating point and memory bandwidth performance from the Knights Landing processors.
1) DDR memory technology enables memory subsystems to transfer data at twice the frequency of single data rate memory by transferring data on both the rising and falling edges of the clock. This improves performance but also makes the design and debugging more challenging due to reduced timing margins.
2) Debugging DDR memory modules requires examining components like the PLL to ensure proper clock generation and alignment, termination resistors to optimize timing, and registers to confirm signals are latched within specifications. Tuning elements like feedback capacitors and resistors can help optimize timing.
3) Testing tools are needed to thoroughly evaluate DDR memory, including memory testers, stress tests, and equipment to measure clock signals on DIMMs independently of a system
Supermicro Servers with Micron DDR5 & SSDs: Accelerating Real World WorkloadsRebekah Rodriguez
This document provides an overview of Supermicro's comprehensive server portfolio, including their rackmount, cloud, and mainstream server solutions. It highlights several multi-node server platforms like BigTwin, FatTwin, and GrandTwin. The document also mentions Supermicro will have many options for the upcoming 4th generation AMD EPYC 'Genoa' platform with support for up to 96 cores, 128 PCIe lanes, and DDR5 memory at up to 6TB capacity. In summary, the document outlines Supermicro's server product lines and upcoming support for the high-end 4th generation AMD EPYC processors.
Memory_Unit Cache Main Virtual AssociativeRNShukla7
The document discusses different types of computer memory organization including memory hierarchy, main memory, auxiliary memory, associative memory, cache memory, and virtual memory. It provides details on RAM and ROM chips used in main memory and how they are connected to the CPU through address and data buses. It also describes different memory mapping techniques used in cache memory including direct mapping, set-associative mapping, and associative mapping.
Internet of Things (IoT) data frequently has a location and time component. Getting value out of this "geotemporal" data can be tricky. We'll explore when and how to leverage Cassandra, DSE Search and DSE Analytics to surface meaningful information from your geotemporal data.
CXL is enabling new memory architectures by connecting CPUs and GPUs to shared memory pools. Early CXL 1.1 focused on memory expansion by connecting processors to DRAM modules. CXL 2.0 allowed for small memory pools accessible by a few servers. CXL 3.0 supports larger shared memory fabrics by connecting thousands of nodes and enabling true shared memory regions accessible coherently by multiple hosts and accelerators. However, shared memory fabrics using CXL 3.0 may experience greater latency variability and congestion compared to single-host or small memory pooling configurations.
DataStax: Extreme Cassandra Optimization: The SequelDataStax Academy
Al has been using Cassandra since version 0.6 and has spent the last few months doing little else but tune Cassandra clusters. In this talk, Al will show how to tune Cassandra for efficient operation using multiple views into system metrics, including OS stats, GC logs, JMX, and cassandra-stress.
Implementation of Dense Storage Utilizing HDDs with SSDs and PCIe Flash Acc...Red_Hat_Storage
At Red Hat Storage Day New York on 1/19/16, Red Hat partner Seagate presented on how to implement dense storage using HDDs with SSDs and PCIe flash accelerator cards.
During the CXL Forum at OCP Global Summit, MemVerge CEO Charles Fan presented accomplishments of the CXL industry since 2019, the development of concept cars occurring today, and his predictions for the future of CXL
Ceph Day Shanghai - SSD/NVM Technology Boosting Ceph Performance Ceph Community
This document discusses using SSDs and emerging non-volatile memory technologies like 3D XPoint to boost performance of Ceph storage clusters. It outlines how SSDs can be used as journals and caches to significantly increase throughput and reduce latency compared to HDD-only clusters. A case study from Yahoo showed that using Intel NVMe SSDs with caching software delivered over 2x throughput and half the latency with only 5% of data cached. Future technologies like 3D NAND and 3D XPoint will allow building higher performance, higher capacity SSDs that could extend the use of Ceph.
This document discusses memory design considerations for system-on-chip and board-based systems. It begins by explaining that memory system performance largely depends on the memory placement (on-die or off-die), access time, and bandwidth. It then provides an overview of different memory technologies that can be used for on-chip and external memory, such as SRAM, DRAM, flash memory, and discusses their characteristics. The document emphasizes that on-die memory allows faster access times compared to off-die memory, and discusses cache memory design approaches to compensate for longer off-die memory access times.
Q1 Memory Fabric Forum: ZeroPoint. Remove the waste. Release the power.Memory Fabric Forum
Nilesh Shah provide an overview of the ZeroPoint portable, hardware IP portfolio for lossless memory compression and compaction. The IP boosts memory capacity 2-4x, bandwidth and performance/watt by 50%, and is 1,000x faster than competitors.
Q1 Memory Fabric Forum: Building Fast and Secure Chips with CXL IPMemory Fabric Forum
Gary Ruggles, Sr Product Manger for PCIe and CXL Controller IP, provides an provides example use cases for adoption of CXL, an introduction to Synopsys CXL IP Solutions, interop and proof points.
Q1 Memory Fabric Forum: CXL-Related Activities within OCPMemory Fabric Forum
OCP steering committee member, and former President of the CXL Consortium, Siamak Tavallaei, provides an overview of CXL-related activities happening within the Open Compute Project.
Q1 Memory Fabric Forum: CXL Controller by Montage TechnologyMemory Fabric Forum
For CXL AIC and memory module designers, Nilesh Shah of Montage provides and overview of their CXL memory controller product, technology, and performance.
Nick Kriczsky and Gorden Getty provide an overview of Teledyne LeCroy’s Austin Labs portfolio of products to services including: 1) testing for protocol and electrical compliance, interoperability, data integrity, and performance, 2) In depth protocol training (PCIe, USB, NVMe, NVMe-oF, Fibre Channel), and 3) Automation (solutions for analysis, jamming, generation)
Q1 Memory Fabric Forum: Memory Fabric in a Composable SystemMemory Fabric Forum
Eddie McMorrow, Sr. Product Manager at GigaIO, defines composable infrastructure and memory fabrics, then provides and overview of the FabreX memory fabric.
MemVerge CEO Charles Fan describes why memory-hungry generative AI is a driver for CXL technology, the new computing model for AI, and MemVerge software for CXL and AI.
Q1 Memory Fabric Forum: Micron CXL-Compatible Memory ModulesMemory Fabric Forum
Michael Abraham, Director of Product Management at Micron, discusses data center challenges, the memory and storage hierarchy, Micron CZ120 memory modules, database (TPC-H) improvements, AI inferencing improvements, and how to enabling in your company.
Q1 Memory Fabric Forum: Compute Express Link (CXL) 3.1 UpdateMemory Fabric Forum
OCP Steering Committee member and ex-President of the CXL Consortium, Siamak Tavallaei, provides an update on the CXL specifications with a focus on the recently released 3.1 specification.
Q1 Memory Fabric Forum: Advantages of Optical CXL for Disaggregated Compute ...Memory Fabric Forum
Ron Swartzentruber, Director of Engineering at Lightelligence, explains why optical connectivity is needed for CXL fabrics, and provides an overview of the Photowave line of port expander PCIe cards and active optical cables.
Arvind Jagannath of VMware makes the case for bridging the CPU-Memory imbalance with memory tiering, describes their vision for memory disaggregation, and explains that VMware will support CXL Expanders – Specific Configurations, Memory Tiering to reduce overall TCO, and Memory Accelerators to enable CXL-based use-cases.
In the CXL Forum Theater at SC23 hosted by MemVerge, Lightelligence describes CXL's need for optical connectivity and their portfolio of CXL optical expander cards and cables
Synopsys: Achieve First Pass Silicon Success with Synopsys CXL IP SolutionsMemory Fabric Forum
This document discusses Synopsys' CXL IP solutions for enabling first pass silicon success. It provides an overview of:
- How large data sets are driving the need for CXL and larger, more efficient cache coherent storage.
- How CXL allows memory expansion by enabling one interface to connect to various memory types like DDR, LPDDR, and persistent memory.
- Synopsys' complete CXL IP solution which uses proven PCIe IP to provide a highly efficient 512-bit controller and 32GT/s PHY for maximum bandwidth and low latency.
- Synopsys' work with XConn to achieve first pass silicon success on a 256 lane CXL 2.0 switch SOC
Project Gismo introduces a global I/O-free shared memory object (Gismo) library that utilizes CXL to provide direct memory access across nodes. This allows distributed applications to access remote objects as fast as local memory, eliminating object serialization and data copying. Demo results show Gismo can improve performance of AI/ML workloads like Ray by up to 675% and reduce database synchronization times. The Gismo API provides functions to connect, create, access, and manage shared memory objects globally without I/O.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
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.
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?
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
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.
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.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdfChart Kalyan
A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
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!
Freshworks Rethinks NoSQL for Rapid Scaling & Cost-EfficiencyScyllaDB
Freshworks creates AI-boosted business software that helps employees work more efficiently and effectively. Managing data across multiple RDBMS and NoSQL databases was already a challenge at their current scale. To prepare for 10X growth, they knew it was time to rethink their database strategy. Learn how they architected a solution that would simplify scaling while keeping costs under control.
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectorsDianaGray10
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
Conversational agents, or chatbots, are increasingly used to access all sorts of services using natural language. While open-domain chatbots - like ChatGPT - can converse on any topic, task-oriented chatbots - the focus of this paper - are designed for specific tasks, like booking a flight, obtaining customer support, or setting an appointment. Like any other software, task-oriented chatbots need to be properly tested, usually by defining and executing test scenarios (i.e., sequences of user-chatbot interactions). However, there is currently a lack of methods to quantify the completeness and strength of such test scenarios, which can lead to low-quality tests, and hence to buggy chatbots.
To fill this gap, we propose adapting mutation testing (MuT) for task-oriented chatbots. To this end, we introduce a set of mutation operators that emulate faults in chatbot designs, an architecture that enables MuT on chatbots built using heterogeneous technologies, and a practical realisation as an Eclipse plugin. Moreover, we evaluate the applicability, effectiveness and efficiency of our approach on open-source chatbots, with promising results.
"Frontline Battles with DDoS: Best practices and Lessons Learned", Igor IvaniukFwdays
At this talk we will discuss DDoS protection tools and best practices, discuss network architectures and what AWS has to offer. Also, we will look into one of the largest DDoS attacks on Ukrainian infrastructure that happened in February 2022. We'll see, what techniques helped to keep the web resources available for Ukrainians and how AWS improved DDoS protection for all customers based on Ukraine experience
Programming Foundation Models with DSPy - Meetup SlidesZilliz
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.
3. Super Computing , Denver, Colorado, 2023
3
Memory Tiering with AutoNUMA for Caching: Redis with
Memtier
Memory capacity expansion through CXL improves Caching
Application’s throughput by ~10X and latency by ~1.8X over DRAM
with SSD configuration
1 1
2.8
3.3
10.3 10.2
0
2
4
6
8
10
12
Ops/sec Total Bandwidth
Normalized
Throughput (higher better)
DRAM + SSD
75% DRAM + 25% CXL w/ AutoNUMA
50% DRAM + 50% CXL w/ AutoNUMA
1 1
0.5
0.6
0.7
0.8
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Cache Allocate P99
Latency
Cache Find P99 Latency
Normalized
Latency (lower better)
DRAM + SSD
75% DRAM + 25% CXL w/ AutoNUMA
50% DRAM + 50% CXL w/ AutoNUMA
EPY
C
CPU
6 x DDR5 DIMM 6 x DDR5 DIMM
4 x DDR4 DIMM on AsteraLabs Leo CXL Card
CXL
32GT/s
System Configuration
50 threads each creating 20 Redis clients
to randomly access cache objects of
total 1TB of working set size
AutoNUMA is used as a page placement
policy for tiered memory
4. Super Computing , Denver, Colorado, 2023
4
Memory Tiering for In-Memory Database: MSSQL with
TPC-H
3.15
2.32 2.18 2.25 2.25 2.27 2.39
4.82 4.71 4.82
4.57 4.69 4.54
4.86
1
6.17 6.84
7.28 7.25 7.28
6.55 6.57
1.32
5.91
6.84
7.31
7.72 7.82
8.24 8.09
0
1
2
3
4
5
6
7
8
9
0 5 10 15 20 25 30 35
Normalized
Execution
Speed
w.r.t.
1
Stream
786GB
DRAM
(12*64GB)
Number of Streams
DRAM Only (12 * 64GB) DRAM Only (12 * 96GB)
DRAM + CXL (12 * 64GB + 1TB) DRAM + CXL (12 * 96GB + 1TB)
1.6X Speedup CXL memory expansion
can improve performance
over DDR module upgrade
at a reduced TCO
in collaboration with Micron
EPY
C
CPU
6 x DDR5 DIMM 6 x DDR5 DIMM
4 x Micron CMM DDR4
CXL
32GT/s
System Configuration
Total working set size is 3TB. For storage, 8x Micron 7450 NVME SSD is used
Linux’s default page placement policy is used for tiered memory management
5. Super Computing , Denver, Colorado, 2023
5
SW-Defined CXL Memory Bandwidth Expansion:
CloverLeaf
CXL memory benefits
HPC applications
through bandwidth
expansion over the DDR
modules
0.63
0.79
1.17
0
0.2
0.4
0.6
0.8
1
1.2
50% DRAM, 50% CXL 64% DRAM, 34% CXL 80% DRAM, 20% CXL
Normalized
Execution
Speedup
SW-Defined Interleaved Page Allocation Ratio
17% Speedup
DRAM Baseline
in collaboration with Micron
EPY
C
CPU
6 x DDR5 DIMM 6 x DDR5 DIMM
4 x Micron CMM DDR4
CXL
32GT/s
System Configuration
NUMA 0
NUMA 1
EPY
C
CPU
6 x DDR5 DIMM 6 x DDR5 DIMM
4 x Micron CMM DDR4
CXL
32GT/s
NUMA 0
NUMA 2
NUMA 1
EPY
C
CPU
6 x DDR5 DIMM 6 x DDR5 DIMM
4 x Micron CMM DDR4
CXL 32GT/s
NUMA 0
NUMA 4
NUMA 1
NUMA 2
NUMA 3
50% DRAM, 50% CXL 64% DRAM, 34% CXL 80% DRAM, 20% CXL
NPS4
NPS2
NPS1