The rapid pace of technological progress has brought unprecedented opportunities for innovation, communication and productivity. However, with increasing reliance on technology comes an increasing risk of cyber attacks. Cyber security has become one of the most pressing issues of our time, affecting individuals, businesses and governments around the world. The consequences of cyber attacks can range from financial loss to disruption of critical infrastructure and even loss of human life.
In recent years, we have witnessed a number of high-profile cyber attacks, including the WannaCry ransomware attack that affected hundreds of thousands of computers worldwide, the Equifax data breach that exposed the confidential information of millions of individuals, and the SolarWinds supply chain attack that involved multiple government agencies and private companies. These incidents highlight the seriousness of the cyber threat situation and the need for effective cyber security measures.
The current state of cyber security
Despite significant efforts to improve online security, the current state of cyber security remains precarious. Cyber attacks are becoming more sophisticated, more frequent and more influential. Cybercriminals are constantly developing new attack methods and exploiting vulnerabilities in software and hardware systems.
Moreover, the COVID-19 pandemic has created new opportunities for cyber attacks. With the rapid shift to remote working and online services, organisations are more vulnerable than ever to cyber attacks. Phishing attacks, ransomware attacks and other forms of cyber attacks have increased during the pandemic.
The most common cyber threats
There are many cyber risks that individuals, companies and governments should be aware of. Here are the most common risks involved:
Malware – is a type of malware that is designed to damage computer systems or steal sensitive information. Typical types of malware are viruses or Trojans.
Ransomware – is a type of malware that is designed to extort money by blocking access to files or a computer system until a ransom is paid.
Phishing – is a type of social engineering attack in which cybercriminals use emails, phone calls or text messages to trick people into divulging sensitive information or clicking on a malicious link.
Distributed Denial of Service (DDoS) attacks – involves flooding a website or server with traffic, causing it to crash and make it unavailable to users.
Man-in-the-middle attacks – these occur when an attacker intercepts and alters communications between two parties in order to steal sensitive information or inject malicious code.
Zero-day exploits – these are vulnerabilities in software or hardware that are unknown to the manufacturer and therefore not patched. Cybercriminals can exploit these vulnerabilities to gain unauthorised access to systems or data.
Challenges of cyber security
There are several challenges to achieving effective cyber security. One of the primary challenges is the shortage of qualified cyber security professionals. The cyber security industry is experiencing a significant shortage of skilled professionals, making it difficult for organisations to find and hire qualified experts to protect their systems.
Another challenge is the complexity of modern technology systems. With
with the proliferation of IoT (’Internet of Things’) devices, cloud computing and other emerging technologies, the attack surface has increased significantly, and this makes detecting and responding to cyber attacks more difficult.
Emerging technologies and strategies
Despite these challenges, there are emerging technologies and strategies that offer hope for a more secure future. For example, artificial intelligence (AI) and machine learning (ML) can be used to detect and respond to cyber threats in real time. Blockchain technology has the potential to increase data security and privacy, while quantum computing may enable us to develop more secure encryption methods.
In addition, organisations are taking a more proactive approach to cyber security. This includes the implementation of security measures such as multi-factor authentication, employee training and awareness programmes and continuous monitoring and testing of systems.
Summary
In summary, cyber security is a critical issue that affects all aspects of our lives. Cyber attacks have the potential to cause significant damage. However, there are new technologies and strategies that offer hope for a safer future. By working together, we can overcome cyber security challenges and build a safer, more protected digital world.
Mogą Ciebie zainteresować
AMD EPYC 7643 z rodziny Milan został dostrzeżony w bazie benchmarku Geekbench. Tam pokazał moc drzemiącą w rdzeniach opartych na mikroarchitekturze Zen 3. Okazuje się, że jeden procesor uzyskał lepszy wynik w teście w porównaniu do platformy składającej się z podwójnego Intel Xeon.
Czy Intel ma jeszcze szanse?
Administratorzy sieci uzyskują w rozwiązaniach SDN w każdej chwili pełen wgląd w jej topologię, co pozwala na lepszą i automatyczną
alokację ruchu sieciowego, szczególnie w okresach wzmożonej transmisji danych. Sieci SDN pomagają zmniejszyć koszty
operacyjne i wydatki kapitałowe
Zwykle możesz chcieć unikać kart graficznych, które były używane przez całą dobę do kopania kryptowaluty. Ale niekoniecznie tak jest w przypadku wielkiego niedoboru GPU, kiedy najlepsze karty graficzne są zawsze niedostępne, nawet jeśli mają wygórowane ceny.
/HPE FRONTIER – World’s Most Powerful Supercomputer
The Hewlett Packard Enterprise (HPE) Frontier supercomputer is one of the most powerful supercomputers in the world. It was developed in collaboration with the US Department of Energy (DOE) and is located at Oak Ridge National Laboratory in Tennessee, US. The Frontier supercomputer is designed to help scientists solve the most complex and pressing problems in a variety of fields, including medicine, climate science and energy.
Technical specifications
The HPE Frontier supercomputer is built on the HPE Cray EX supercomputer architecture, which consists of a combination of AMD EPYC processors and NVIDIA A100 GPUs. It has a peak performance of 1.5 exaflops (one quintillion floating point operations per second) and can perform more than 50,000 trillion calculations per second. The system has 100 petabytes of storage and can transfer data at up to 4.4 terabytes per second.
Applications
The HPE Frontier supercomputer is used for a wide range of applications, including climate modelling, materials science and astrophysics. It is also used to develop new drugs and treatments for diseases such as cancer and COVID-19.
Climate modelling
The Frontier supercomputer is being used to improve our understanding of the Earth’s climate system and to develop more accurate climate models. This will help scientists predict the impacts of climate change and develop mitigation strategies.
Materials science
The supercomputer is also being used to model and simulate the behaviour of materials at the atomic and molecular level. This will help scientists develop new materials with unique properties such as increased strength, durability and conductivity.
Astrophysics
The Frontier supercomputer is being used to simulate the large-scale behaviour of the universe, including the formation of galaxies and the evolution of black holes. This will help scientists better understand the nature of the universe and the forces that govern it.
Drug development
The supercomputer is being used to simulate the behaviour of biological molecules, such as proteins and enzymes, in order to develop new drugs and treatments for diseases. This will help scientists identify new targets for drug development and develop more effective treatments for a wide range of diseases.
Summary
The HPE Frontier supercomputer represents a major step forward in the development of high performance computing. Its unprecedented computing power and storage capacity make it a valuable tool for researchers in many fields. Its ability to simulate complex systems at a high level of detail helps us better understand the world around us and develop solutions to some of the most pressing challenges facing humanity.
Mogą Ciebie zainteresować
AMD EPYC 7643 z rodziny Milan został dostrzeżony w bazie benchmarku Geekbench. Tam pokazał moc drzemiącą w rdzeniach opartych na mikroarchitekturze Zen 3. Okazuje się, że jeden procesor uzyskał lepszy wynik w teście w porównaniu do platformy składającej się z podwójnego Intel Xeon.
Czy Intel ma jeszcze szanse?
Administratorzy sieci uzyskują w rozwiązaniach SDN w każdej chwili pełen wgląd w jej topologię, co pozwala na lepszą i automatyczną
alokację ruchu sieciowego, szczególnie w okresach wzmożonej transmisji danych. Sieci SDN pomagają zmniejszyć koszty
operacyjne i wydatki kapitałowe
Zwykle możesz chcieć unikać kart graficznych, które były używane przez całą dobę do kopania kryptowaluty. Ale niekoniecznie tak jest w przypadku wielkiego niedoboru GPU, kiedy najlepsze karty graficzne są zawsze niedostępne, nawet jeśli mają wygórowane ceny.
/NVIDIA H100 – Revolutionary Graphics Accelerator for High Performance Computing
NVIDIA, a leading graphics processing unit (GPU) manufacturer, has unveiled the NVIDIA h100, a revolutionary GPU gas pedal designed for high-performance computing (HPC). This groundbreaking gas pedal is designed to meet the demands of the most demanding workloads in the fields of artificial intelligence (AI), machine learning (ML), data analytics and more.
Construction
NVIDIA h100 is a powerful GPU gas pedal that is based on NVIDIA’s Ampere architecture. It is designed to deliver unparalleled performance for HPC workloads and can support a wide range of applications, from deep learning to scientific simulation. The h100 is built on the NVIDIA A100 Tensor Core GPU, which is one of the most powerful GPUs available on the market today.
Features
NVIDIA H100 comes with several features that set it apart from other GPU gas pedals on the market. Some of the most notable features are:
High performance: the NVIDIA H100 is designed to provide the highest level of performance for HPC workloads. It features 640 Tensor cores that offer up to 1.6 teraflops of performance in double precision mode and up to 3.2 teraflops of performance in single precision mode.
Memory bandwidth: the H100 has 320 GB/s of memory bandwidth, allowing it to easily handle large data sets and complex calculations.
NVLink: The h100 also supports NVIDIA’s NVLink technology, which allows multiple GPUs to work together as a single unit. This enables faster data transfer and processing between GPUs, which can significantly increase performance in HPC workloads.
Scalability: the NVIDIA H100 is highly scalable and can be used in a wide variety of HPC applications. It can be deployed in both on-premises and cloud environments, making it a flexible solution for organizations of all sizes.
Comparison
When comparing the NVIDIA h100 to other GPU gas pedals on the market, there are a few key differences to consider. Here is a brief comparison between the NVIDIA H100 gas pedal and some of its top competitors:
NVIDIA H100 vs. NVIDIA A100: The NVIDIA h100 is built on the same architecture as the A100, but has twice the memory bandwidth and is optimized for HPC workloads.
NVIDIA H100 vs. AMD Instinct MI100: The h100 outperforms the MI100 in terms of single precision performance, memory bandwidth and power efficiency.
NVIDIA H100 vs. Intel Xe-HP: h100 is designed specifically for HPC workloads, while Xe-HP is more versatile and can be used in a wider range of applications.
Summary
Overall, the NVIDIA H100 is a powerful and versatile GPU gas pedal that is designed for high-performance computing workloads. Its high performance, memory bandwidth and NVLink support make it an excellent choice for organizations that require superior computing power. Compared to top competitors, the h100 excels in HPC optimization and scalability, making it an excellent choice for organizations of all sizes.
Mogą Ciebie zainteresować
AMD EPYC 7643 z rodziny Milan został dostrzeżony w bazie benchmarku Geekbench. Tam pokazał moc drzemiącą w rdzeniach opartych na mikroarchitekturze Zen 3. Okazuje się, że jeden procesor uzyskał lepszy wynik w teście w porównaniu do platformy składającej się z podwójnego Intel Xeon.
Czy Intel ma jeszcze szanse?
Administratorzy sieci uzyskują w rozwiązaniach SDN w każdej chwili pełen wgląd w jej topologię, co pozwala na lepszą i automatyczną
alokację ruchu sieciowego, szczególnie w okresach wzmożonej transmisji danych. Sieci SDN pomagają zmniejszyć koszty
operacyjne i wydatki kapitałowe
Zwykle możesz chcieć unikać kart graficznych, które były używane przez całą dobę do kopania kryptowaluty. Ale niekoniecznie tak jest w przypadku wielkiego niedoboru GPU, kiedy najlepsze karty graficzne są zawsze niedostępne, nawet jeśli mają wygórowane ceny.
/Virtual Machine – What Is It And Why Is It So Useful?
Many of today’s cutting-edge technologies such as cloud computing, edge computing and microservices, owe their start to the concept of the virtual machine—separating operating systems and software instances from the underlying physical computer.
What is a virtual machine?
A virtual machine (VM) is software that runs programs or applications without being tied to a physical machine. In a VM instance, one or more guest machines can run on a host computer.Each VM has its own operating system, and functions separately from other VMs, even if they are located on the same physical host. VMs generally run on servers, but they can also be run on desktop systems, or even embedded platforms. Multiple VMs can share resources from a physical host, including CPU cycles, network bandwidth and memory.
VMs trace their origins to the early days of computing in the 1960s when time sharing for mainframe users was used to separate software from a physical host system. A virtual machine was defined in the early 1970s as “an efficient, isolated duplicate of a real computer machine.”
VMs as we know them today have gained steam over the past 20 years as companies adopted server virtualization in order to utilize the compute power of their physical servers more efficiently, reducing the number of physical servers and saving space in the data center. Because apps with different OS requirements could run on a single physical host, different server hardware was not required for each one.
How do VMs work?
In general, there are two types of VMs: Process VMs, which separate a single process, and system VMs, which offer a full separation of the operating system and applications from the physical computer. Examples of process VMs include the Java Virtual Machine, the .NET Framework and the Parrot virtual machine.
Virtual Machine, the .NET Framework and the Parrot virtual machine. System VMs rely on hypervisors as a go-between that give software access to the hardware resources. The hypervisor emulates the computer’s CPU, memory, hard disk, network and other hardware resources, creating a pool of resources that can be allocated to the individual VMs according to their specific requirements. The hypervisor can support multiple virtual hardware platforms that are isolated from each other, enabling VMs to run Linux and Windows Server OSes on the same physical host.
Big names in the hypervisor space include VMware (ESX/ESXi), Intel/Linux Foundation (Xen), Oracle (MV Server for SPARC and Oracle VM Server for x86) and Microsoft (Hyper-V). Desktop computer systems can also utilize virtual machines. An example here would be a Mac user running a virtual Windows instance on their physical Mac hardware.
What are the two types of hypervisors?
The hypervisor manages resources and allocates them to VMs. It also schedules and adjusts how resources are distributed based on how the hypervisor and VMs have been configured, and it can reallocate resources as demands fluctuate. Most hypervisors fall into one of two categories:
Type 1 – A bare-metal hypervisor runs directly on the physical host machine and has direct access to its hardware. Type 1 hypervisors typically run on servers and are considered more efficient and better-performing than Type 2 hypervisors, making them well suited to server, desktop and application virtualization. Examples of Type 1 hypervisors include Microsoft Hyper-V and VMware ESXi.
Type 2 – Sometimes called a hosted hypervisor, a Type 2 hypervisor is installed on top of the host machine’s OS, which manages calls to the hardware resources. Type 2 hypervisors are generally deployed on end-user systems for specific use cases. For example, a developer might use a Type 2 hypervisor to create a specific environment for building an application, or a data analyst might use it to test an application in an isolated environment. Examples include VMware Workstation and Oracle VirtualBox.
What are the advantages of virtual machines?
Because the software is separate from the physical host computer, users can run multiple OS instances on a single piece of hardware, saving a company time, management costs and physical space. Another advantage is that VMs can support legacy apps, reducing or eliminating the need and cost of migrating an older app to an updated or different operating system. In addition, developers use VMs in order to test apps in a safe, sandboxed environment. Developers looking to see whether their applications will work on a new OS can utilize VMs to test their software instead of purchasing the new hardware and OS ahead of time. For example, Microsoft recently updated its free Windows VMs that let developers download an evaluation VM with Windows 11 to try the OS without updating a primary computer. This can also help isolate malware that might infect a given VM instance. Because software inside a VM cannot tamper with the host computer, malicious software cannot spread as much damage.
What are the downsides of virtual machines?
Virtual machines do have a few disadvantages. Running multiple VMs on one physical host can result in unstable performance, especially if infrastructure requirements for a particular application are not met. This also makes them less efficient in many cases when compared to a physical computer. And if the physical server crashes, all of the applications running on it will go down. Most IT shops utilize a balance between physical and virtual systems.
What are some other forms of virtualization?
The success of VMs in server virtualization led to applying virtualization to other areas including storage, networking, and desktops. Chances are if there’s a type of hardware that’s being used in the data center, the concept of virtualizing it is being explored (for example, application delivery controllers). In network virtualization, companies have explored network-as-a-service options and network functions virtualization (NFV), which uses commodity servers to replace specialized network appliances to enable more flexible and scalable services. This differs a bit from software-defined networking, which separates the network control plane from the forwarding plane to enable more automated provisioning and policy-based management of network resources. A third technology, virtual network functions, are software-based services that can run in an NFV environment, including processes such as routing, firewalling, load balancing, WAN acceleration, and encryption. Verizon, for example, uses NFV to power its Virtual Network Services that enables customers to spin up new services and capabilities on demand. Services include virtual applications, routing, software-defined WANs, WAN optimization and even Session Border Controller as a Service (SBCaaS) to centrally manage and securely deploy IP-based real-time services, such as VoIP and unified communications.
VMs and containers
The growth of VMs has led to further development of technologies such as containers, which take the concept another step and is gaining appeal among web application developers. In a container setting, a single application along with its dependencies, can be virtualized. With much less overhead than a VM, a container only includes binaries, libraries, and applications. While some think the development of containers may kill the virtual machine, there are enough capabilities and benefits of VMs that keep the technology moving forward. For example, VMs remain useful when running multiple applications together, or when running legacy applications on older operating systems. In addition, some feel that containers are less secure than VM hypervisors because containers have only one OS that applications share, while VMs can isolate the application and the OS. Gary Chen, the research manager of IDC’s Software-Defined Compute division, said the VM software market remains a foundational technology, even as customers explore cloud architectures and containers. “The virtual machine software market has been remarkably resilient and will continue to grow positively over the next five years, despite being highly mature and approaching saturation,” Chen writes in IDC’s Worldwide Virtual Machine Software Forecast, 2019-2022.
VMs, 5G and edge computing
VMs are seen as a part of new technologies such as 5G and edge computing. For example, virtual desktop infrastructure (VDI) vendors such as Microsoft, VMware and Citrix are looking at ways to extend their VDI systems to employees who now work at home as part of a post-COVID hybrid model. “With VDI, you need extremely low latency because you are sending your keystrokes and mouse movements to basically a remote desktop,” says Mahadev Satyanarayanan, a professor of computer science at Carnegie Mellon University. In 2009, Satyanarayanan wrote about how virtual machine-based cloudlets could be used to provide better processing capabilities to mobile devices on the edge of the Internet, which led to the development of edge computing. In the 5G wireless space, the process of network slicing uses software-defined networking and NFV technologies to help install network functionality onto VMs on a virtualized server to provide services that once ran only on proprietary hardware. Like many other technologies in use today, these emerging innovations would not have been developed had it not been for the original VM concepts introduced decades ago.
Mogą Ciebie zainteresować
AMD EPYC 7643 z rodziny Milan został dostrzeżony w bazie benchmarku Geekbench. Tam pokazał moc drzemiącą w rdzeniach opartych na mikroarchitekturze Zen 3. Okazuje się, że jeden procesor uzyskał lepszy wynik w teście w porównaniu do platformy składającej się z podwójnego Intel Xeon.
Czy Intel ma jeszcze szanse?
Administratorzy sieci uzyskują w rozwiązaniach SDN w każdej chwili pełen wgląd w jej topologię, co pozwala na lepszą i automatyczną
alokację ruchu sieciowego, szczególnie w okresach wzmożonej transmisji danych. Sieci SDN pomagają zmniejszyć koszty
operacyjne i wydatki kapitałowe
Zwykle możesz chcieć unikać kart graficznych, które były używane przez całą dobę do kopania kryptowaluty. Ale niekoniecznie tak jest w przypadku wielkiego niedoboru GPU, kiedy najlepsze karty graficzne są zawsze niedostępne, nawet jeśli mają wygórowane ceny.
Supermicro Ultra SuperServer® is Supermicro’s 11th generation high performance general purpose server. The Ultra is designed to provide the highest performance, flexibility, scalability and serviceability in demanding IT environments, as well as to power critical corporate workloads.
Unmatched performance: support for two 2nd Generation Intel® Xeon® Scalable processors with up to 28 cores per socket and up to 6TB of ECC DDR4 memory in 24 DIMM slots with Intel® Optane “¢ DCPMM support, the Ultra is designed to support demanding and complex loads. The Ultra is available in NVMe all-flash configurations where users can benefit from reduced latency and increased IOP. With NVMe, it is possible to increase storage latency up to 7x and increase throughput by up to 6x.1 The ROI benefits of NVMe deployments are immediate and significant.
Exceptional flexibility: discover the freedom to adapt to different loads with the versatile Supermicro Ultra system. Improve your server environment with the perfect combination of computing power, memory and storage performance, network flexibility and serviceability. This highly scalable system provides excellent expansion and storage options thanks to our patented vertical system. With support for multiple PCIe add-on cards, the Ultra Future protects your business against ever-changing computation and storage. This Ultra server is designed to handle any workload in any number of demanding environments.
Continuous reliability and serviceability: Achieve higher levels of high availability and data storage with the latest Intel® Xeon® Scalable processors, ECC DDR4 memory modules, NVMe-enabled disk bays, and energy-efficient redundant power supplies. Designed from the ground up as an enterprise class, the Ultra is fully equipped with energy-efficient components and built-in redundancy.
Supermicro Ultra Servers are designed to give the greatest possible power, flexibility and scalability. It is a great choice to meet the most demanding operations in Enterprise, Data Center and Cloud Computing environments.
Mogą Ciebie zainteresować
AMD EPYC 7643 z rodziny Milan został dostrzeżony w bazie benchmarku Geekbench. Tam pokazał moc drzemiącą w rdzeniach opartych na mikroarchitekturze Zen 3. Okazuje się, że jeden procesor uzyskał lepszy wynik w teście w porównaniu do platformy składającej się z podwójnego Intel Xeon.
Czy Intel ma jeszcze szanse?
Administratorzy sieci uzyskują w rozwiązaniach SDN w każdej chwili pełen wgląd w jej topologię, co pozwala na lepszą i automatyczną
alokację ruchu sieciowego, szczególnie w okresach wzmożonej transmisji danych. Sieci SDN pomagają zmniejszyć koszty
operacyjne i wydatki kapitałowe
Zwykle możesz chcieć unikać kart graficznych, które były używane przez całą dobę do kopania kryptowaluty. Ale niekoniecznie tak jest w przypadku wielkiego niedoboru GPU, kiedy najlepsze karty graficzne są zawsze niedostępne, nawet jeśli mają wygórowane ceny.
Over the past few years, data security has become a priority topic among business owners. Through the development of technology, more and more sectors are being digitized, not only improving the operation of the company, but also exposing it to attacks from cyber criminals. We can’t provide 100% protection for confidential information, but by putting the right steps in place, we can minimize the risk of a potential leak. As a result, both the company’s good name and budget will not suffer.
In an era that condones employees to use private devices for business purposes, security issues have never been so sensitive. Surveys show that only 40% of working people in Poland consider issues related to protecting the equipment they work on. This poses quite a challenge for owners of businesses, who must ensure not only the security of the data itself, but also systematize regulations in relation to the surveillance of their subordinates’ private devices. We need to realize the consequences that can accompany a data leak – even if we run a small or medium-sized company. Leakage of customers’ private information, caused either by the deliberate actions of external hackers or by an employee who took advantage of an unlucky open Wi-Fi network, can cost our company exorbitant sums of money (leaving aside the risk of possible liability under, for example, data protection regulations).
The potential threat may not only come from the network – it also applies to theft or damage to physical equipment. That’s why we should make an effort to ensure that vital equipment for the operation of the company is properly secured, especially against the possibility of outside contact. In terms of data protection, establishing adequate oversight is much more crucial. The basis is choosing the right security system – one that is tailored to our company. It is at this stage that it is crucial to establish a data hierarchy, so that access to the most important information for the company, such as confidential customer data, will be reserved for those with authorizations – that is, employees for whom such knowledge is absolutely necessary to perform their duties. Let’s also ask ourselves an important question – what will we do if somehow this data is lost? If we do not yet know the answer, let’s think as soon as possible about separate a team whose task will be to periodically create backups and properly secure them. This way, in case of an attack and deletion of information or ordinary failure, we will be able to recover the data. The most perfect system will not work if it is not used by competent people. That’s why it’s so important to sensitize the employees themselves to device security issues. Let’s start by making a list of of tasks that all subordinates will have to perform before integrating their device into company operations, and another one describing cyclical procedures (such as updating or frequently changing passwords). Employees’ knowledge will be based on this, while separate training and each time introducing new people to the company’s security routine may be necessary to fully implement the security requirements.
Like any professional solution, a surveillance system for confidential information first requires prudent planning. We do not have to deal with this ourselves – there are companies that professionally deal with assisting companies in implementing security measures. However, we should remember to use common sense in this matter as well: when deciding on the services of specialists, be sure that they really are the best at what they do. In the age of the Internet, we can get opinions on almost any service provider, a good old recommendation by a friendly company will also work. Thanks to all these measures, we will be able to sleep peacefully, and our company – to function without unpleasant surprises.
Mogą Ciebie zainteresować
AMD EPYC 7643 z rodziny Milan został dostrzeżony w bazie benchmarku Geekbench. Tam pokazał moc drzemiącą w rdzeniach opartych na mikroarchitekturze Zen 3. Okazuje się, że jeden procesor uzyskał lepszy wynik w teście w porównaniu do platformy składającej się z podwójnego Intel Xeon.
Czy Intel ma jeszcze szanse?
Administratorzy sieci uzyskują w rozwiązaniach SDN w każdej chwili pełen wgląd w jej topologię, co pozwala na lepszą i automatyczną
alokację ruchu sieciowego, szczególnie w okresach wzmożonej transmisji danych. Sieci SDN pomagają zmniejszyć koszty
operacyjne i wydatki kapitałowe
Zwykle możesz chcieć unikać kart graficznych, które były używane przez całą dobę do kopania kryptowaluty. Ale niekoniecznie tak jest w przypadku wielkiego niedoboru GPU, kiedy najlepsze karty graficzne są zawsze niedostępne, nawet jeśli mają wygórowane ceny.
Nvidia is a company known for producing high-performance graphics cards and gaming hardware, but the company is also making waves in the data centre space with its Nvidia Data Centre platform. The platform offers a set of hardware and software products designed to accelerate data centre workloads, from machine learning and AI to scientific computing and virtual desktop infrastructure.
Hardware offer
At the heart of the Nvidia Data Centre platform is a line of data centre GPUs, including the A100, V100 and T4. These chips are optimised to accelerate a wide range of workloads, from training deep learning models to running virtual desktops. They offer high levels of parallelism and performance, and are designed to be scalable and meet the needs of large data centers. In addition to GPUs, Nvidia also offers a range of data centre hardware products, including the DGX A100 system, which combines eight A100 GPUs with NVLink connectivity technology to deliver high performance computing and storage in a single server.
Software offer
In addition to its hardware products, Nvidia also offers a suite of software products designed to help data centre operators manage and optimise their workloads. This includes the Nvidia GPU Cloud (NGC), which provides a repository of pre-trained deep learning models, as well as tools to deploy and manage GPU-accelerated workloads. Nvidia also offers a range of software tools for managing and optimising GPU performance, including the Nvidia CUDA Toolkit, which provides a set of libraries and APIs for developing GPU-accelerated applications, and the Nvidia GPU Management Toolkit, which provides tools for monitoring and optimising GPU performance in data centre environments.
Use cases
The Nvidia Data Center platform is used across a wide range of industries and applications, from scientific computing and weather forecasting to financial services and healthcare. For example, the platform is used by the National Center for Atmospheric Research to perform high-resolution climate change simulations and by the Centers for Disease Control and Prevention to analyse genomic data to identify disease outbreaks. In the financial services industry, the Nvidia Data Centre platform is used to run complex risk simulations and predictive analytics models, while in healthcare it is used to accelerate medical imaging and drug discovery research.
Summary
The Nvidia Data Centre Platform offers a powerful set of hardware and software products designed to accelerate data centre workloads across a wide range of industries and applications. With a focus on GPU acceleration and high-performance computing, the platform is well suited for machine learning and artificial intelligence workloads, as well as scientific computing and virtual desktop infrastructure. As data centre workloads grow in complexity and scale, the Nvidia Data Centre platform is likely to play an increasingly important role in accelerating data centre performance and enabling new applications and use cases.
Mogą Ciebie zainteresować
AMD EPYC 7643 z rodziny Milan został dostrzeżony w bazie benchmarku Geekbench. Tam pokazał moc drzemiącą w rdzeniach opartych na mikroarchitekturze Zen 3. Okazuje się, że jeden procesor uzyskał lepszy wynik w teście w porównaniu do platformy składającej się z podwójnego Intel Xeon.
Czy Intel ma jeszcze szanse?
Administratorzy sieci uzyskują w rozwiązaniach SDN w każdej chwili pełen wgląd w jej topologię, co pozwala na lepszą i automatyczną
alokację ruchu sieciowego, szczególnie w okresach wzmożonej transmisji danych. Sieci SDN pomagają zmniejszyć koszty
operacyjne i wydatki kapitałowe
Zwykle możesz chcieć unikać kart graficznych, które były używane przez całą dobę do kopania kryptowaluty. Ale niekoniecznie tak jest w przypadku wielkiego niedoboru GPU, kiedy najlepsze karty graficzne są zawsze niedostępne, nawet jeśli mają wygórowane ceny.
Switches are an essential part of computer networks, providing a way of connecting devices together to allow communication between them. A switch is a network device that connects devices on a local area network (LAN) to allow them to communicate with each other. Switches operate at the data link layer of the OSI model, which is the second layer of the seven-layer model. This layer is responsible for the reliable transfer of data between network devices.
Basic information about switches
Switches come in different types and configurations, with varying capabilities and performance characteristics. The most common types are:
Unmanaged – these switches are the simplest type and are typically used in small networks. They provide basic connectivity between devices and cannot be configured.
Managed – these devices offer more advanced features such as VLANs (Virtual Local Area Networks), QoS (Quality of Service) and port mirroring. They can be configured to optimise network performance and security.
Layer 3 switches – these switches are also known as routing switches because they can route traffic between different subnets or VLANs. They are more expensive than other types of these devices, but are essential in larger networks.
Switches can be further classified based on their architecture, such as:
Modular Switches – these switches allow more ports or features to be added by adding modules to the switch.
Fixed Switches – these devices come with a fixed number of ports and features that cannot be changed or upgraded.
Stackable Switches – these can be stacked to create a single, larger switch with more ports.
Switches use a variety of technologies to enable communication between devices, such as:
The most common technology used in switches is Ethernet. This is a set of standards for transmitting data over a LAN.
Spanning Tree Protocol (STP) is a protocol used in switches to prevent loops in the network. It works by disabling redundant links between switches, ensuring that there is only one active path between any two devices.
Virtual Local Area Networks (VLANs). VLANs enable the creation of logical networks within a physical network. This provides security and performance benefits by distributing traffic between different groups of devices.
When it comes to choosing a network switch for an organisation, there are several factors to consider, including performance, scalability, reliability and cost. The three main players in the switch market are Cisco, Dell and IBM. Let’s take a closer look at each of these companies and their switch offerings to see how they compare.
Cisco
Cisco is a dominant player in the networking industry and offers a wide range of switch models designed for businesses of all sizes. Their switches are known for their high performance, reliability and advanced features such as virtualisation and security.
One of Cisco’s flagship switch models is the Catalyst series, which offers a range of options for different network sizes and requirements. Catalyst switches are designed for data centre, campus and branch office environments and can support up to 10Gbps per port. Catalyst switches are also equipped with advanced security features such as access control lists (ACLs), port security and MAC address filtering.
Another popular Cisco switch series is the Nexus series, which is designed for high-performance data centre environments. Nexus switches can support up to 40Gbps per port and offer advanced features such as virtualisation, storage networking and high availability.
Dell
Dell is another big player in the switch market, offering a range of switch models for small and medium-sized businesses. Dell switches are known for their ease of use, affordability and scalability.
One of Dell’s popular switch ranges is the PowerConnect series, which offers a range of options for different network sizes and requirements. PowerConnect devices are designed for small and medium-sized businesses and can support up to 10Gbps per port. PowerConnect switches are also equipped with advanced features such as VLAN support, link aggregation and QoS.
Another popular Dell switch series is the N-Series, which is designed for high-performance data centre environments. The N-series switches can support up to 40Gbps per port and offer advanced features such as virtualisation, storage networking and high availability.
IBM
IBM is also a major player in the switch market, offering a range of enterprise-level switch models. IBM switches are known for their advanced features, high performance and reliability.
One of IBM’s flagship switch models is the System Networking RackSwitch series, which offers a range of options for networks of different sizes and requirements. RackSwitches are designed for data centre environments and can support up to 40Gbps per port. RackSwitch devices are also equipped with advanced features such as virtualisation, storage networking and high availability.
Another popular IBM switch series is the System Networking SAN series, which is designed for storage area network (SAN) environments. Such switches can support up to 16Gbps per port and offer advanced features such as Fabric Vision technology, which provides real-time visibility and monitoring of this environment.
Summary
Overall, each of these switch manufacturers offers a range of models to meet the needs of businesses of different sizes and requirements. When selecting such a device, factors such as performance, scalability, reliability and cost should be considered, as well as the specific features and capabilities offered by each switch model.
Mogą Ciebie zainteresować
AMD EPYC 7643 z rodziny Milan został dostrzeżony w bazie benchmarku Geekbench. Tam pokazał moc drzemiącą w rdzeniach opartych na mikroarchitekturze Zen 3. Okazuje się, że jeden procesor uzyskał lepszy wynik w teście w porównaniu do platformy składającej się z podwójnego Intel Xeon.
Czy Intel ma jeszcze szanse?
Administratorzy sieci uzyskują w rozwiązaniach SDN w każdej chwili pełen wgląd w jej topologię, co pozwala na lepszą i automatyczną
alokację ruchu sieciowego, szczególnie w okresach wzmożonej transmisji danych. Sieci SDN pomagają zmniejszyć koszty
operacyjne i wydatki kapitałowe
Zwykle możesz chcieć unikać kart graficznych, które były używane przez całą dobę do kopania kryptowaluty. Ale niekoniecznie tak jest w przypadku wielkiego niedoboru GPU, kiedy najlepsze karty graficzne są zawsze niedostępne, nawet jeśli mają wygórowane ceny.
/Artificial Intelligence – Significant Help Or Threat?
Artificial Intelligence (AI) is a rapidly developing technology that is changing the way we live and work. From virtual assistants and chatbots to cars that drive themselves and analyse the traffic situation and smart homes, AI is already having a significant impact on our daily lives and sometimes we don’t even realise it. In this article, we will explore the development of AI, the emergence of GPT chatbots and the opportunities and risks posed by this technology.
The development of artificial intelligence
AI has been developed for decades, but recent advances in machine learning and deep learning have greatly accelerated its progress. Machine learning is a type of artificial intelligence that allows computers to learn from data without explicit programming. Deep learning is a subset of machine learning that uses artificial neural networks to simulate the way the human brain works.
As a result of these advances, AI is now able to perform tasks that were once thought impossible, such as image recognition and natural language processing. These capabilities have opened up a wide range of new applications for AI, from healthcare and finance to transport and entertainment.
GPT chat
One of the most exciting developments related to artificial intelligence is the emergence of GPT chat. This acronym stands for 'Generative Pre-trained Transformer’, a type of AI model that can generate human-like responses to questions we ask it. This technology has been used to create chatbots that can talk to users in a natural and engaging way, just as if we were writing with a human.
GPT chat has many potential applications, from customer service and sales to mental health support and education. It could also be used to create virtual companions or assistants who could provide emotional support or help with everyday tasks.
Threats posed by the development of artificial intelligence
The development of artificial intelligence has the potential to revolutionise many areas of our lives, but it also poses significant risks. Here are some of the key risks arising from the development of AI:
Displacement of jobs – as AI becomes more capable, it could replace many jobs that are currently performed by humans. This could lead to widespread unemployment and economic disruption, particularly in industries that rely heavily on manual labour or routine tasks.
Bias and discrimination – AI algorithms are only as unbiased as the data they are trained on. If the data is biased or incomplete, the algorithm may produce biased or discriminatory results. This can lead to unfair treatment of individuals or groups, especially in areas such as hiring, lending and criminal justice.
Security and privacy risks – as AI becomes more ubiquitous, it also becomes a more attractive target for cyber attacks. AI systems can also be used to launch cyber attacks, such as phishing or social engineering attacks. In addition, AI systems can collect and analyse vast amounts of personal data, which raises privacy and data security concerns.
Autonomous weapons – AI technology can be used to create autonomous weapons that can make decisions about who to target and when. This could lead to an arms race where countries seek to develop increasingly sophisticated AI-powered weapons, potentially leading to catastrophic conflict.
Existential risk – some experts have raised concerns about the possibility of a 'technological singularity’ in which AI becomes so powerful that it surpasses human intelligence and becomes uncontrollable. This could lead to a number of catastrophic consequences, such as the complete subjugation of humanity or the extinction of the human race.
Opportunities arising from the development of AI
The development of AI offers many potential opportunities in many areas. Here are some of the key opportunities that may arise from the continued development of AI:
Improved efficiency and productivity – AI has the potential to automate many tasks that are currently performed manually, leading to increased efficiency and productivity. This can lead to lower costs and higher profits for businesses, as well as more free time for people who previously performed this task manually.
Improved decision-making – artificial intelligence can process vast amounts of data and make predictions and recommendations based on that data. This can help individuals and organisations make more informed decisions, particularly in areas such as healthcare, finance and transport.
Personalisation and customisation – AI can be used to analyse data about individuals and personalise products and services based on their preferences and needs. This can lead to better customer experiences and increased loyalty.
Improved healthcare – AI can be used to analyse medical data and identify patterns and trends that could lead to more accurate diagnoses and more effective treatments. AI-powered medical devices could also help to monitor and treat patients more effectively.
Environmental sustainability – AI can be used to optimise energy consumption, reduce waste and improve resource allocation, leading to a more sustainable future.
Scientific discovery – AI can be used to analyse large data sets and identify patterns that can lead to new scientific discoveries and breakthroughs.
Enhanced safety and security – AI can be used to detect and prevent cyber attacks, improve public safety and help law enforcement identify and apprehend criminals.
Summary
AI is a rapidly evolving technology that is changing the world in many ways. The emergence of GPT chatbots is just one example of AI’s incredible potential. However, it also poses some significant risks, such as the potential impact on workplaces and the risk of misuse. It is important to continue to develop AI responsibly and to carefully consider the opportunities and risks that the technology presents.
Mogą Ciebie zainteresować
AMD EPYC 7643 z rodziny Milan został dostrzeżony w bazie benchmarku Geekbench. Tam pokazał moc drzemiącą w rdzeniach opartych na mikroarchitekturze Zen 3. Okazuje się, że jeden procesor uzyskał lepszy wynik w teście w porównaniu do platformy składającej się z podwójnego Intel Xeon.
Czy Intel ma jeszcze szanse?
Administratorzy sieci uzyskują w rozwiązaniach SDN w każdej chwili pełen wgląd w jej topologię, co pozwala na lepszą i automatyczną
alokację ruchu sieciowego, szczególnie w okresach wzmożonej transmisji danych. Sieci SDN pomagają zmniejszyć koszty
operacyjne i wydatki kapitałowe
Zwykle możesz chcieć unikać kart graficznych, które były używane przez całą dobę do kopania kryptowaluty. Ale niekoniecznie tak jest w przypadku wielkiego niedoboru GPU, kiedy najlepsze karty graficzne są zawsze niedostępne, nawet jeśli mają wygórowane ceny.
The development of edge computing technology has revolutionized the way we think about data processing and storage. With the growing demand for faster and more efficient access to data and applications, edge computing has emerged as a savior of sorts. In this article, we will explore the concept of edge computing in servers, including its definition, history and applications. We will also discuss the features, advantages and disadvantages of this solution in servers, as well as the latest trends and technologies in this field.
What is Edge Computing?
Edge computing is a distributed computing model that brings data processing and storage closer to where it is needed in order to reduce latency and increase performance. This concept was first introduced in 2014 and has since gained popularity due to the growth of the Internet of Things (IoT) and the need for real-time data processing.
History of Edge Computing
The origins of edge computing can be traced to the concept of distributed computing, which dates back to the 1970s. However, the specific term „edge computing” was coined in 2014 by Cisco, which recognized the need for a new computing model to support the growing number of IoT devices.
How Edge Computing Works
Edge computing involves deploying small, low-power computers, known as edge devices, at the edge of the network, closer to where the data is generated. These edge devices process and store data locally, and send only the most relevant data to the cloud for further processing and storage. This reduces the amount of data that must be sent to the cloud, thereby reducing latency and improving response time.
Edge Computing in Servers
Edge computing is increasingly being used in servers, especially in the context of edge data centers. Edge data centers are smaller data centers that are located closer to end users to provide faster access to data and applications. By deploying edge servers in these locations, enterprises can improve the performance of their applications and reduce latency.
Features of Edge Computing in Servers
Edge computing in servers offers a number of key features, including:
Low latency – by processing data locally, edge servers can provide real-time responses to users.
Scalability – Edge servers can easily scale up or down as needed, allowing companies to respond quickly to changes in demand.
Security – by processing data locally, edge servers can help improve data security and privacy, as sensitive data does not need to be transmitted over the network.
Cost efficiency – by reducing the amount of data that must be sent to the cloud, edge computing can help reduce the cost of cloud storage and processing.
Benefits of Edge Computing in Servers
Edge computing in servers offers a number of benefits to businesses, including:
Improved performance – by reducing latency and improving response time, edge computing can help companies deliver faster and more responsive applications.
Improved reliability – by processing data locally, edge servers can help ensure that applications remain operational even if connectivity to the cloud is lost.
Increased flexibility – by deploying edge servers, companies can choose to process data locally or in the cloud, depending on specific needs.
Enhanced security – by processing data locally, edge servers can help improve data security and privacy.
Disadvantages of Edge Computing in servers
While edge computing in servers offers many benefits, there are also some potential disadvantages to consider. These include:
Increased complexity – deploying edge servers requires careful planning and management, and can increase the complexity of the overall IT infrastructure.
Higher costs – deploying edge servers can be more expensive than relying solely on cloud infrastructure, due to the need to purchase and maintain additional hardware.
Limited processing power – edge servers may have limited processing power compared to cloud servers, which may affect their ability to handle large amounts of data.
Summary
Edge computing is a powerful technology that can help enterprises improve the performance, reliability and security of their applications. By deploying edge servers, companies can enjoy the benefits of edge computing while taking advantage of the scalability and cost-effectiveness of cloud computing. However, it is important to carefully consider the potential advantages and disadvantages of edge computing before deciding to implement it.
Mogą Ciebie zainteresować
AMD EPYC 7643 z rodziny Milan został dostrzeżony w bazie benchmarku Geekbench. Tam pokazał moc drzemiącą w rdzeniach opartych na mikroarchitekturze Zen 3. Okazuje się, że jeden procesor uzyskał lepszy wynik w teście w porównaniu do platformy składającej się z podwójnego Intel Xeon.
Czy Intel ma jeszcze szanse?
Administratorzy sieci uzyskują w rozwiązaniach SDN w każdej chwili pełen wgląd w jej topologię, co pozwala na lepszą i automatyczną
alokację ruchu sieciowego, szczególnie w okresach wzmożonej transmisji danych. Sieci SDN pomagają zmniejszyć koszty
operacyjne i wydatki kapitałowe
Zwykle możesz chcieć unikać kart graficznych, które były używane przez całą dobę do kopania kryptowaluty. Ale niekoniecznie tak jest w przypadku wielkiego niedoboru GPU, kiedy najlepsze karty graficzne są zawsze niedostępne, nawet jeśli mają wygórowane ceny.
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