#Datacentric

[techblog-365]

WHAT IS THE PURPOSE OF DATA SCIENCE?

Data Science's main aim is to identify trends inside data. In order to Analyze and draw lessons from the results, it utilizes different statistical techniques. A Data Scientist should carefully scrutinize the information from data acquisition, wrangling and pre-processing. Then, from the details, he has the duty to make predictions. To read more visit: https://www.rangtech.com/blog/data-science/what-is-the-purpose-of-data-science

[mlops-courses]

Building The Superior Data-Centric MLOps Best Practices

Key Points:

Data-Centric Approach: High-quality data is essential for accurate and reliable AI models.

Automation: Automating tasks streamlines the ML lifecycle and reduces errors.

Collaboration: Effective teamwork is crucial for successful MLOps implementation.

Continuous Monitoring: Monitor models for performance, drift, and resource utilization.

Version Control: Track changes and ensure model reproducibility.

Scalability: Design your MLOps pipeline to handle growing data volumes and user bases.

https://aitech.studio/aie/mlops-best-practices/

[daemonhxckergrrl]

starfleet engineering:

backup systems for basically everything (except warp cores)

backup systems for the backup systems

modular everything !!

tight tolerances for everything

backup systems for the backup systems' backup systems

maximum safe ratings far below maximum capable ratings

circumvention techniques as standard protocol (why use standard authorisation when you can override ? why modify components when you can just bypass them ?)

assorted beep boops and blinkenlights

backup systems for the backup systems' backu.......

[sgnog]

𝗧𝗥𝗔𝗡𝗦𝗙𝗢𝗥𝗠𝗜𝗡𝗚 𝗗𝗔𝗧𝗔 𝗖𝗘𝗡𝗧𝗥𝗘𝗦 𝗙𝗢𝗥 𝗔𝗜

GPUs significantly increase the demand of data centre (DC) infrastructure resources. Hear 𝗵𝗼𝘄 @meta 𝗲𝗻𝗮𝗯𝗹𝗲𝗱 𝗔𝗜 in its existing DC infrastructure.

𝗥𝗲𝗴𝗶𝘀𝘁𝗲𝗿 𝗵𝗲𝗿𝗲: https://sgnog.net/?page_id=7025

[govindhtech]

Micron 9550 NVMe SSD: Powering the Future of Data Centers

The fastest data Centre SSD in the world

As the fastest SSD for data centre storage in the world, the Micron 9550 NVMe SSD outperforms rivals.

Designed to handle vital tasks including artificial intelligence (AI), performance-focused databases, caching, online transaction processing (OLTP), and high-frequency trading that demand extraordinary speed, scalability, and power efficiency. These workloads and more are made possible by the Micron 9550 NVMe SSD for flexible deployment in OEM, cloud, data centre, and system integrator architectures. With a maximum storage capacity of 30.72TB, the Micron 9550 SSD contributes to the achievement of ideal storage density.

Broad Open Compute Project (OCP) 2.0 compatibility is built into the Micron 9550 SSD, and extra OCP 2.5 support is available for adding comprehensive telemetry data logging to track the SSD’s health and performance. In addition to delivering cloud-scale AI capabilities to enterprise data centres, OCP offers intelligent management tools to optimise and proactively address typical data centre challenges.

With important security features including SPDM 1.2, SHA-512, and RSA standards, the Micron 9550 helps protect your data. For extra protection, Micron offers specialised processing hardware with physical separation through its Secure Execution Environment (SEE).

Advantages Micron 9550 NVMe SSD

Increased productivity and efficiency for tasks with a lot of data

Achieving 14.0 GB/s sequential reads and 10.0 GB/s sequential writes, the Micron 9550 offers best-in-class performance. This outstanding speed up to 67% faster than comparable SSDs from competitors helps guarantee unparalleled performance for taxing workloads.

The perfect SSD for  artificial intelligence

More power and performance are required for AI applications, and this drive is designed to handle the most taxing workloads. Utilising NVIDIA technology, the Micron 9550 surpasses competitors in terms of power efficiency and  AI task performance thanks to Big Accelerator Memory (BaM). It uses up to 43% less average SSD power while delivering up to 60% quicker feature aggregation performance and up to 33% faster task completion times.

Vertical integration and the newest features are provided by Micron innovation NVIDIA

Micron-designed DRAM, NAND, firmware, and controller ASIC are integrated in the Micron 9550. NVMe 2.0 and OCP 2.0 are supported, along with OCP 2.5 for telemetry data logging.2. Its end-to-end security capabilities, which include encryption, SED, SPDM 1.2, and SEE, protect data.

Data centres need storage systems that can adapt to the rapid changes in industry and innovation brought about by artificial intelligence (AI). Please welcome their latest drive, the Micron 9550 NVMe SSD, to meet this demand. This innovative vertically integrated SSD employs Micron’s industry-leading 232-layer NAND and PCIe Gen5 technology. Cutting edge Micron technologies improve performance and power efficiency. Fast and power-efficient, the Micron 9550 NVMe SSD is the fastest PCIe Gen5x4 data centre SSD. It’s not only fast, though.

The Micron 9550 is a highly efficient and quick device.

With PCIe Gen5 technology, the Micron 9550 SSD offers industry-leading speeds and an incredible performance. With the Micron 9550, you can:

Sequential read performance of up to 14 GB/s is a notable improvement in data transfer speeds that leads the industry.

With a sequential write capability of up to 10 GB/s, it outperforms other PCIe Gen5 drives on the market by up to 67%.

Up to 3.3 million IOPS random read performance 35% better than competitors.

Up to 400,000 IOPS of random write performanceup to 33% faster than competitive solutions.

AI: The PCIe Gen5 application that kills

The need for high-performance storage solutions is being driven by AI, which has emerged as PCIe Gen5′s killer application. AI model sizes are increasing, and with them comes the need for effective data processing. These demands are too much for traditional file access techniques, which result in high overhead and latency. Big Accelerator Memory (BaM), a novel storage software solution, is being developed to exploit SSDs for direct, fine-grain access as GPU threads to big training models and vast datasets, in order to overcome this difficulty.

Direct storage device access is made possible without the need for CPU intervention via BaM’s unique storage driver, which is optimised for parallel GPU processing. This leads to optimised IOPS and a notable decrease in training durations for workloads such as graph neural networks (GNN), which depend on tiny, random read operations across big datasets.

BaM has proven its abilities by optimising input/output operations per second (IOPS) and drastically reducing GNN training times. We set a new benchmark for AI data processing speed and efficiency with their testing of BaM on the Micron 9550.

Performance and sustainability come together

The Micron 9550 SSD is a noteworthy example of sustainability due to its exceptional performance as well as its much higher energy efficiency, which is important for AI applications. Micron testing data shows that the Micron 9550 NVMe SSD beats its rivals by up to 60% in GNN training using BaM, while using up to 43% less energy per SSD. This means that an amazing 29% less system energy is needed to do the same task.

See their technical brief on Micron 9550 NVME SSD and Big Accelerator Memory (BaM) for more information.

Comparably, their testing on large language model inference shown up to 15% better performance with the Micron 9550 SSD while preserving up to 37% of the energy per drive, translating into up to 19% system energy savings

Read more on govindhtech.com

[ifitechsolu1pg2]

Our Solutions - IFI Techsolutions | Microsoft Solutions Partner.

IFI Techsolutions is a Microsoft Solutions Partner, We provide Digital & App Innovation, Infrastructure, Modern Work, Data & AI, DevOps, Cloud Migration, etc.

[sifytech]

Feeling the Heat: The Evolution of Data Centre Cooling

The debate about how data centre cooling systems should be designed has been raging for decades. Read More. https://www.sify.com/data-centers/feeling-the-heat-the-evolution-of-data-centre-cooling/

[trishayadav695-blog]

"Discover peace of mind in the digital age with Intelics Data Security. At https://intelics.com/, we redefine the boundaries of protection, offering cutting-edge solutions to safeguard your most critical assets. Our data security protocols are not just about defense; they're a fortress against potential threats, ensuring your information stays confidential and resilient. Intelics stands at the forefront of innovation, employing state-of-the-art encryption, secure storage, and proactive monitoring to shield your data from evolving cyber risks. Trust us to empower your digital journey with robust, reliable, and responsive data security. Explore the future of safeguarding information – explore Intelics today."

[techblog-365]

How Telecom Industry is Shaping up for the next generation using Data Science

[lilliankillthisman]

There may not in the event be any great change in the number of office workers in central London over the next decade, or decades. There may even be a mild long-term decline. Mechanisation of office work, and the replacement of the clerk by the computer, could see to that. The computer does in fact take up more space than the clerk. But it does not need to be housed in the same place as the rest of an office. If an insurance company has to have its executives and the core of its staff in the expensive insurance area of the City of London, there is no reason why the computers doing the work of batches of clerks should not be located miles away in Southend.

There's a lot to unpack about this view of the post-1967 future. But obviously the biggest part is the assumption that a computer will take up more space than a human clerk.

[apas-95]

whenever a liberal blames disney homophobia on china I blow up another AO3 datacentre

[123lineengineers]

HELP DESK/IT SUPPORT TECHNICAL TEST PREPARATION

https://youtube.com/watch?v=HaZR5p8zzuQ Read the full article

[govindhtech]

Intel Xeon 6 E-core Processors for Gamers and Creators

Intel Xeon 6 E-core

Intel revealed state-of-the-art technologies and architectures today at Computex that have the potential to significantly accelerate the AI ecosystem from the data centre, cloud, and network to the edge and PC. With increased processing power, cutting-edge power efficiency, and an affordable total cost of ownership (TCO), clients may now take use of the full potential of AI systems.

AI Data Centres Benefit from Intel Xeon 6 Processors

Companies are under increasing pressure to update their outdated data centre systems in order to maximise physical floor and rack space, save costs, meet sustainability targets, and develop new digital capabilities throughout the organisation as digital transformations pick up speed.

With both Intel Xeon 6 E-core (Efficient-core) and P-core (Performance-core) SKUs to address the wide range of use cases and workloads, from AI and other high-performance compute needs to scalable cloud-native applications, the Xeon 6 platform and processor family as a whole were designed with these issues in mind. Built on a shared software stack and an open ecosystem of hardware and software manufacturers, E-cores and P-cores share a compatible architecture.

The Intel Xeon 6 E-core, code-named Sierra Forest, is the first of the Xeon 6 CPUs to be released and will be available starting today. The Xeon 6 P-cores, also known as Granite Rapids, should be released the following quarter.

The Intel Xeon 6 E-core processor offers good performance per watt and a high core density, allowing for efficient computing at much lower energy costs. For the most demanding high-density, scale-out workloads, such as cloud-native apps and content delivery networks, network microservices, and consumer digital services, the enhanced performance with higher power efficiency is ideal.

Furthermore, when compared to 2nd Gen Intel Xeon processors on media transcoding tasks, Intel Xeon 6 E-core enormous density advantages allow for rack-level consolidation of 3-to-1, giving clients a rack-level performance gain of up to 4.2x and performance per watt gain of up to 2.6×1. Xeon 6 processors free up computational capability and infrastructure for creative new AI applications by consuming less power and rack space.

Intel Gaudi AI Accelerators Improve GenAI Performance at Lower Cost

These days, it’s getting cheaper and quicker to use generative AI. The industry standard for infrastructure, x86 runs at scale in almost all data centre environments and provides the basis for integrating AI capabilities while guaranteeing affordable interoperability and the enormous advantages of an open community of developers and users.

When used in conjunction with Intel Gaudi AI accelerators, which are specifically intended for AI applications, Intel Xeon processors make the best CPU head node for AI workloads. When combined, these two provide a potent solution that blends in well with the current infrastructure.

For training and inference of large language models (LLM), the Gaudi architecture is the only MLPerf-bench marked substitute for Nvidia H100 that offers customers the desired GenAI performance at a price-performance advantage that offers choice, quick deployment, and a lower total cost of operation.

System providers can purchase a basic AI kit for $65,000, which includes eight Intel Gaudi 2 accelerators and a universal baseboard (UBB). This kit is anticipated to be one-third less expensive than equivalent competitor platforms. Eight Intel Gaudi 3 accelerators with a UBB will be included in a kit that will retail for $125,000; this is around two-thirds less than comparable competition platforms.

With the help of Intel Gaudi 3 accelerators, businesses will be able to extract more value from their unique data by achieving notable performance gains for training and inference workloads on top GenAI models. According to projections, Intel Gaudi 3 in a 8,192-accelerator cluster will provide up to 15% better training throughput for a 64-accelerator cluster compared to Nvidia H100 on the Llama2-70B model and up to 40% faster time-to-train compared to the equal size Nvidia H100 GPU cluster. Furthermore, it is anticipated that Intel Gaudi 3 will provide up to two times quicker inferencing on average when compared to Nvidia H100 while running widely used LLMs like Mistral-7B and Llama-70B.

Intel is working with at least ten of the leading international system providers, including six new companies that just stated they will be releasing Intel Gaudi 3, to make these AI systems widely accessible. Leading system providers Dell, HPE, Lenovo, and Supermicro now have more production options thanks to new partners Asus, Foxconn, Gigabyte, Inventec, Quanta, and Wistron.

Revolutionary laptop AI architecture triples compute and power efficiency

Intel is expanding its AI presence outside of the data centre, both in the PC and at the edge. Intel has been enabling enterprise choice for decades with more than 200 million CPUs deployed to the ecosystem and more than 90,000 edge deployments.

Intel is leading the charge in this category-creating moment as the AI PC category is revolutionising every facet of the computing experience today. The goal now is to create edge devices that learn and change in real time, anticipating user requirements and preferences and ushering in a completely new era of productivity, efficiency, and creativity. It is no longer just about faster processing speeds or sleeker designs.

By 2028, 80% of PC sales are expected to come from AI models, according to Boston Consulting Group. Intel reacted swiftly, enabling over 100 independent software vendors (ISVs), 300 features, and support for 500 AI models throughout its Core Ultra platform, to provide the best hardware and software platform for the AI PC.

Building swiftly on these unparalleled benefits, the company today unveiled the Lunar Lake architecture, which serves as the flagship processor for the upcoming AI PC generation. Lunar Lake is expected to provide up to 40% reduced SoC power and more than three times the AI compute, thanks to a significant leap in graphics and AI processing power and an emphasis on capability-efficient compute performance for the thin-and-light market. It is anticipated to ship in 2024’s third quarter, just in time for the Christmas shopping season.

The brand-new architecture of Lunar Lake will allow for:

The new Performance-cores (P-cores) and Efficient-cores improve performance and energy efficiency.

A fourth-generation Intel NPU with 48 tera-operations per second (TOPS) AI capabilities. Improves in generative AI are made possible by this potent NPU, which provides up to 4x AI compute compared to the previous iteration.

The brand-new X2 GPU cores for visuals and the X Matrix Extension (XMX) arrays for AI are combined in the Battlemage GPU design. The new XMX arrays provide a second AI accelerator with up to 67 TOPS of performance for exceptional throughput in AI content production, while the X2 GPU cores increase gaming and graphics performance by 1.5x over the previous version.

Amazing laptop battery life is made possible by an innovative compute cluster, an advanced low-power island, and Intel innovation that manages background and productivity tasks extremely well.

Intel is already shipping at scale, delivering more AI PC processors through the first quarter of 2024 than all competitors combined, while others get ready to join the AI PC market. More than 80 distinct AI PC designs from 20 original equipment manufacturers (OEMs) will be powered by Lunar Lake. This year, Intel anticipates putting more than 40 million Core Ultra processors on the market.

Read more on govindhtech.com

[ianmoyse]

Removing Technology Roadblocks For The Decade Ahead

Ian Moyse – Industry Cloud Thought Leader Having worked in the IT sector for 3 decades, in the past 5 years I have witnessed faster change and adoption of technologies than the prior 20 years combined. Users’ familiarity with technology have rocketed, and their demands have evolved alongside. Much of this has been driven by the consumerisation of compute power in smart phones, home IoT devices…