Dedicated GPU For Cloud Servers

Dedicated GPU Cloud Servers

It is pleased to announce the new Dedicated GPU option specially designed for users with intensive and special computing needs. Users can harness the full power of dedicated GPU to achieve ultra-high performance computing cloud servers specialized in Data Parallel Computation, Machine Learning and Graphically-Intensive Projects.

Machine Learning

GPU is widely used in deep learning because of the strong capability of parallel computing. Compared to CPU, GPU has much more cores to learn representations automatically from data such as images, video or text. Thus, it helps to reduce machine learning training time from days to minutes, enabling researchers and developers to obtain faster, more accurate information from deep learning.

Graphically Demanding Applications

Besides, GPU is effective in video and image rendering. The long rendering time is always a major issue to creative professionals that tied up computing resources and stifled creative flow. Modern GPUs enable and accelerate the cloud servers to process video and graphic in higher-definition formats. Obviously, it is also powerful in computationally intensive gaming, providing gamers with smoother and higher-quality gaming experience.


LayerStack offers NVIDIA® Tesla T4 GPU for intensive users. T4 is a high rating GPU with 2560 CUDA cores and 320 Tensor cores, it has 16GB GDDR6 Memory and 40 RT core. Work together with best-in-class AMD EPYC2 CPU to deliver the best cloud performance for most demanding applications.


We very much value your feedback for future developments, please let us know your comments and suggestions on LayerStack Community.

The Differences Between High Frequency CPU and Dedicated CPU Cloud Servers

Differences of CPU-Focused Cloud Servers Plans

To cope with diverse needs in cloud solutions and improve users’ cloud experience, LayerStack has made significant updates to the offers in Q4 2020. It newly launched two cloud servers plans, the High Frequency CPU Cloud Servers and Dedicated CPU Cloud Servers. It is no doubt that both of them are specially designed for CPU demanding workloads and applications, so what are the differences between the two new plans? This blog will identify the differences and provide some use cases for cloud users.

High Frequency CPU Cloud Servers

Effective in AI and machine learning

Launched in October 2020, it utilizes top-class 2nd Gen AMD EPYC with a turbo boost of 3.4 GHz which is the fastest architecture available on LayerPanel. It is specially designed for applications that rely heavily on computing speed and faster data processing. Moreover, dedicated GPU will be available soon for users who are seeking ultimate ML performance on High Frequency CPU Cloud Server.

CPU Comparison

According to the CPU comparison conducted recently, CPUs applied in LayerStack’s cloud servers are scoring 71362 and 67185 by PassMark which are way ahead of the processors used by other top cloud providers. Obviously, LayerStack’s High Frequency CPU Cloud Servers is utilizing top-level processors in the cloud industry. Users’ most demanding workloads can be handled rapidly with superior clock speeds, large bandwidth, and fast I/O transfers.

Dedicated CPU Cloud Server

Suitable for latency-sensitive applications

Launched in Nov 2020, it is powered by another AMD EPYC2 which can be boosted up to 3.3GHz in turbo mode. The CPU cores are dedicated to specific servers that users can harness the full power of the CPU for their workloads. This servers plan is specially designed for long-running or latency-sensitive applications that require significant computing power to support.

Use Case

Although both new plans are CPU-related providing users with strong computing power, they are best suit in different cases. High Frequency CPU Cloud Servers is very effective in compute-intensive applications like machine learning, computer aided design (CAD) and video encoding. Dedicated CPU Cloud Server, on the other hand, is performing well in long-running projects, technical analysis, CI/CD and batch Processing.


Let us know your comments and suggestions on LayerStack Community.

Why Should You Adopt Cloud Servers?

Why Should You Adopt Cloud Servers? Benefits of Cloud Servers.

Cloud Servers has been a business trend for years. With cloud servers, documents and applications can be accessed through the internet on a quicker basis, cloud users can also practice Virtual desktop infrastructure (VDI) with any smart device for remote working.

It is accounted that more than 85% of businesses worldwide are making use of cloud technology to store and process data. In fact, 67% of enterprise has already turned into cloud-based. It is not surprising that the numbers keep rising today and cloud computing will become even more common in the coming future (Bulao, 2020) .

Below are some reasons why you should definitely adopt cloud solutions:

Reduce Cost

Reduce Cost with cloud servers

It is commonly agreed that application of cloud servers is able to help the organizations to cut cost which is the major reason for most of the enterprise moving workloads to the cloud. Companies can save costs from several aspects such as IT infrastructure, Energy cost, IT specialist and Data security. You can reach another blog article HERE for more details.


Scalable Cloud Server

Scalability is another selling point of cloud servers. It may involve big investments and some time-consuming workloads to activate a physical machine, and that time lost may eventually affect your businesses. However, it takes only 5 mins to resize cloud servers to perfectly meet the changing needs and traffic spikes in a simple and cost-effective way.

Data Privacy and Security

Data Privacy and Security

Data security is the major concerns resisting businesses to apply cloud solutions. However, cloud servers are proved to be more secure than legacy system in most cases. Many cloud services possess different security solution like Firewalls, DDoS Attack Protection, Online Backup, Private Networking. You can reach another article HERE for more details.

Cloud Management

Simple Cloud Management

Cloud providers are responsible for the cloud management, once there is any error occurred, the trained specialist would respond immediately. Thus, employers do not need to worry about the IT training and the potential of human error which may lead to businesses disasters. Moreover, cloud users may apply backup solutions to prevent possible data corruption.


The business environment is changing rapidly, more and more workloads were moving to online to meet the changing needs. This move has been speeded up due to the outbreak of Covid-19, remote working has become more common today. Surely, there are many benefits for businesses to apply cloud computing solutions which are not discussed in this article. It is no doubt that you should get on board now and start enjoying the benefits of this megatrend!


Let us know your comments and suggestions on LayerStack Community.

Dedicated CPU Cloud Server

Dedicated CPU Cloud Server Official Launch

It is pleased to announce the launch of our new cloud server plan – the Dedicated CPU Cloud Server. Same as other LayerStack cloud servers, it is powered by 2nd Gen AMD EPYC 64-Core CPU to deliver high cloud performance for most of the general and CPU-intensive workloads especially for the ones need sustainable computing support like machine learning. In contrast to standard servers, dedicated CPU server is installed with entire CPU cores that are accessible only by your instances, thus your software and applications can always run at peak speed.

Dedicated CPU’s Specifications

The selected 2nd Gen AMD EPYC processor has 64 cores and supports 128 threads with a TDP of 225W. The base clock speed is 2.0GHz which can be boosted up to 3.3GHz in turbo mode. It works perfectly on diverse tasks relying on CPU power, such as analytics, app development, CAE/CFD/FEA ERM/SCM/CRM apps, VDI and many more.

Cloud Computing with Second Gen AMD EPYC (EPYC2) 64-Core CPU

Benefits of AMD EPYC on Cloud Server
High and Better Cloud Performance

The AMD EPYC™ processor secure root of trust is designed to validate the initial BIOS enabling software boot without corruption. It also helps safeguard privacy and integrity by encrypting each virtual machine with up to 509 unique encryption keys known only to the processor.


Most Common Use Case of Dedicated CPU Plan
Common Use Case of Dedicated CPU VPS

Harness the full power of the CPU for applications and workloads. Fast loading and responsive applications in the absence of other clients competing for computing power. Scalable on-demand and intended for heavy workloads, such as AI, machine learning, CI/CD, batch processing, and video encoding.

New High Frequency CPU Plan & CPU Comparison

New High Frequency CPU Plan & Cloud Providers' CPU Comparison

LayerStack is coming up with an exciting, one-of-a-kind High Frequency CPU Server Plan unmatched in the cloud-computing industry. Applications that depend upon higher computing power, faster network speeds, and lightning access to storage infrastructure will significantly benefit from the plan. The plan utilizes high-rating CPU – the AMD EPYC 7742 which boasts a superior performance with 64 cores and 128 threads. It comes with a high base clockspeed of 2.25 GHz, capable of a turbo boost up to 3.4 GHz. The 2nd generation EPYC processor is based on Zen 2 microarchitecture, with a TDP of 225 W and built on the 7 nm process technology.

Uses of High Frequency CPU Server

CPU-optimized cloud Servers handle high-performance computing workloads

High Frequency CPU Servers handle high-performance computing (HPC) workloads easily due to their superior clock speeds, large bandwidth, and fast I/O transfers. The ability to perform quadrillions of calculations is immensely useful in data-sensitive applications, hyper-converged infrastructure, increased VM density, and processing complex calculations with humongous data in real-time.


Common use case of CPU-optimized Cloud Server

The EPYC server series provides the computing backbone for Google Cloud, Amazon Web Services, and Microsoft’s Azure services. Research labs use clusters of high-frequency CPU servers for predicting and tracking storms and testing new products. Live event streaming, rendering mind-blowing special effects, and 3D imaging need powerful CPUs. Artificial intelligence and machine learning use HPC in applications ranging from detecting credit card fraud to teaching self-driving vehicles. Real-time stock trends and automated trading platforms use high-frequency servers extensively.

Comparison of CPU’s used by LayerStack and other top cloud providers.

LayerStack uses AMD’s powerful EPYC series processors in all its plans. According to Passmark’s CPU benchmarking test, LayerStack CPUs’ score is significantly higher than the CPUs selected by most of the top cloud providers, we have picked a few providers and compare the CPU efficiency.

*The comparison below is for reference purpose only, the information may vary due to different cloud server deployment, LayerStack bears no responsibility for any listed information.

Comparison of CPU specification used by top cloud providers

The Standard Plan uses AMD EPYC 7662 and 7702, with clockspeeds between a base 2.0 GHz and max turbo 3.35 GHz. They both have 64 cores and supports 128 threads simultaneously, with a TDP up to 225W.

The High Frequency CPU Plan uses the AMD EPYC 7742 which is highly scored by PassMark Software.

DO Cloud Provider

The Standard Plan uses Intel Xeon E5-2650 v4, with clockspeeds between a base 2.2 GHz and turbo 2.9 GHz. Launched in Q2 2016, the Xeon has 12 cores and supports 24 threads, with a TDP of 105W.

The CPU-optimized Plan uses Intel Xeon Gold, with clockspeeds between a base 2.3 GHz and turbo 3.7 GHz. Launched in Q4 2017, it has 18 cores and supports 36 threads, with a TDP of 140W.

L Cloud Provider

The Standard Plan uses both Intel Xeon E5-2697 v4, with clockspeeds between a base 2.3 GHz and turbo 3.6 GHz, and AMD EPYC 7501 between 2.0 GHz and 3.0 GHz. The Xeon has 18 cores and supports 36 threads, while the 7501 has 32 cores and supports 64 threads.

The Dedicated-CPU Plan uses AMD EPYC 7601, with clockspeeds between a base 2.2 GHz and turbo 2.7 GHz. Launched in Q4 2017, the 7601 has 32 cores and supports 64 threads, with a TDP of 180W.

Comparison Result

PassMark CPU comparison for cloud providers

LayerStack’s EPYC 7702 and 7742 have the highest CPU Mark scores, followed by L Brand’s EPYC 7601 and 7501. DO Brand’s Xeon E5-2560 scores the lowest.
* Let us know your comments and suggestions on LayerStack Community.

LayerStack And 2nd Gen AMD EPYC ™

LayerStack And 2nd Gen AMD EPYC 64 Core CPU

To cope with the demanding workloads, LayerStack maximize the cloud performance with AMD EPYC to deliver the best cloud computing service to our valued customers. Today, AMD dominates the cloud computing market, the 2nd Gen AMD EPYC™ Processors series is specifically designed for cloud-based solutions which sets a higher standard for cloud deployments. Innovative design makes AMD EPYC™ #1 in performance across industry to propel cloud users’ workloads simply and cost-effectively.

LayerStack Cloud Configuration & Use Case

LayerStack Cloud Server CPU Configuration and Use Case

LayerStack cloud servers are configured with top-class AMD EPYC aiming to provide leading cloud efficiency in the industry. It delivers outstanding values for users to manage most of the general and CPU-intensive workloads such as machine learning, video editing, compiling programs and AD serving.


Enhance Performance By High Ranked AMD EPYC

LayerStack standard cloud servers uses 2nd Gen AMD EPYC 64 Core CPU. All selected CPU are with 64 cores and 128 threads and launched after Q3 2019. They runs with base clock speed 2.0 GHz and max. turbo boost 3.4 GHz. Moreover, LayerStack’s coming high frequency CPU servers are configured with AMD EPYC 7742 with higher operating frequency and turbo speed.

CPU Comparison By Geekbench Browser

The new High Frequency CPU Cloud Server (Launch on 27/10/2020) is specially for CPU-intensive cloud usage. We have conducted a simple comparison for the CPU used by top cloud providers with Geekbench Browser on 23rd Oct , a cross-platform processor benchmark to evaluate single-core and multi-core performance. We purchased the most similar optimized-CPU servers with 2 vCPU and 4GB Ram directly from each provider for comparison. It can be seen that LayerStack High Frequency CPU Server is rated the highest with 7919 multi-core score. Vutlr is ranked second with 7820 points. AWS Lightsail and DigitalOcean are at the third and the fourth place with 6246 and 4670 points respectively.


* Let us know your comments and suggestions on LayerStack Community.

Full Geekbench Report of Server’s CPU Performance:
1. LayerStack High Frequency Plan 2. Vultr High Frequency Compute Plan
3. DigitalOcean CPU-Optimized Droplets 4. Amazon Lightsail Plan

Move Backwards From Multi-cloud to Single Cloud Provider?

Why Users Should Move Backwards From Multi-cloud to Single Cloud Provider?

Multi-cloud is the use of two or more cloud providers. Many enterprises divide the businesses into several parts and place in different cloud environment. Although multi-cloud strategy might give businesses extra values, the risks of multi-cloud outweigh the benefits. Placing data in several providers may reduce the data security because securing a multi-cloud environment can be significantly more difficult than with a single cloud provider. In fact, moving the workloads from multiple cloud providers to one can also enhance the efficiency and lower the cost. In this article, it will discuss about the benefits of cloud integration and what solutions are available to keep your data secure.

Save Cost

Single Cloud Save Cost From Multi-Cloud

One key selling points of cloud is the scalability, cloud server can be freely upgraded and downgraded. In fact, the subscription fee of larger-sized server tends to be much cheaper than small-sized server combinations. Besides, cloud users are installing diverse software in servers, the IT expenses of software licenses like antivirus software can be reduced.

Employee Training

Single Cloud Save Employee Training Time

The systems of cloud providers are most likely different, it requires large effort and is time-consuming to train IT staff to control multiple cloud computing platforms. It is also very hard for them to manage the cloud and the data in usual as cloud structure is complicated especially when workloads are involved with hybrid cloud infrastructure and multi-cloud strategy.

Security Concern

Single Cloud Provider's Data Security Solutions

Cloud providers are offering different solutions to protect clients’ data, such as auto-backup and DDoS protection. Auto-backup refers to automatic snapshot of the cloud server that users can restore the servers in any disasters. Due to the big cost saved from single cloud, they can activate these features without any extra investment to enjoy entire protection to the cloud.

Virtual Private Cloud

Global Virtual Private Cloud VPC

For sensitive data, global virtual private cloud (VPC) is an advanced solution for users to keep data like confidential projects, customer information and transaction data. It works with global private network and a true isolated instance. VPC is also effective in safeguarding business from disasters. Data can be real-time mirroring to those isolated instances and work properly to minimize the negative impacts.


* Let us know your comments and suggestions on LayerStack Community.

Why Businesses Should be Looking At Cloud Providers in Singapore for Global Expansion?

Expanding your business is a crucial decision that involves meticulous consideration related to a multitude of factors. When you are considering Asia business expansion, you cannot rule out well-developed world city like Singapore because of infrastructures, tax policies and trade openness, as well as the maturity of data center. Reach the full article at Serchen Blog.

Cloud Computing For Education: Distance Learning

Cloud and Education: Distance Learning

Cloud computing is playing an important role in Education, textbooks and classrooms are no longer a restriction to study. With the Covid-19 outbreaks, the evolution in the education industry has been sped up. Institutions are now applying different distance learning programs, students can access the class anywhere simply with a computing device.

A study shows that the market size of cloud computing in the education industry was USD 8.13 billion in 2016, it is estimated to reach USD 25.36 billion by 2021. This hike is due to large-scale cloud adoptions because of the accessibility, scalability and resource availability of cloud computing.

Improve Educational Productivity
Improve Educational Productivity

Education institutions can move resources to the cloud and makes distance learning practical. Many organizations like universities and training courses start launching e-learning programs so students can take distance courses and online tests instead. In fact, cloud-based system benefit to both e-learning and traditional courses because students can download the resource without geographic restrictions.

Save Cost and Time
Save Cost and Time

Since the resource is available online, teachers no longer need to spend time on printing study materials. Besides printing cost, education organizations can save IT expenses from hardware, IT specialists and energy usage. The University of Notre Dame saved 40 percent ($1.3million) on its annual IT operations. Moreover, it also benefits to students because digital textbook tends to be lot less expensive.

Enhance Teachers’ Accountability

As all the materials are processing online, it is much easier for accountants to calculate teacher’s salaries. The online system may also provides evidences to teachers to get reasonable pay for works. Furthermore, cloud improves the accuracy of teacher’s evaluations as schools recorded all the works. When things go wrong, all resources can be reviewed and the accountability is enhanced in result.


* Let us know your comments and suggestions on LayerStack Community.

Smart Home/Store and Cloud Computing

Smart Home and Cloud Computing

It is no doubt that our world is becoming more intelligent and convenient, many innovated ideas is generated and gradually taking shape over the past 10 years due to the rapid development on AI. Smart home and unmanned shop are the most popular topics among numerous business creatives, they have one thing in common that they both involve with cloud computing in practice. This article will discuss about the position of cloud computing in future intelligent technologies.

Amazon First Unmanned Store
Unmanned Store and Cloud Computing

In Feb 2020, Amazon opened its first unmanned store in Seattle and named it as Amazon Go Grocery. The meaning behind the name is “Grab whatever you want and just go”. No payment process is needed during the shopping experience, all payment will be done automatically on your Amazon account after shopper walking out with the items. The unmanned retail solution relies on integration of RFID technology, infrared sensing technology and video surveillance. Thus, Amazon Go Grocery is a combination of unmanned store and cloud computing technologies, there are numerous cameras and sensors in store tracking shoppers’ movements, all videos will be sent to the cloud for massive analysis as for calculating the total bills. In unmanned store, cloud computing is acting as a professional analyst and accountant.

Role of Cloud Computing in Smart Home
Role of Cloud Computing in Smart Home

The smart home is a concept of the pervasive computing which is gradually becoming the trend of modern house. Although intelligence appliances work with different functions, it is commonly agreed that there is a non-substitutable connection between cloud computing and smart home system. For numerous data and complex control bring about a much heavy burden on the local computers, it is suggested that moving the calculation to the cloud can reduce local workload, meanwhile AI can access real time information through Web browser. For instance, smart refrigerator can order food online automatically once it has connected with cloud computing. Smart toilet, on the other hand, can record your health and send the data to healthy applications for daily analysis.

The Future of Smart Homes

Obviously, cloud computing is playing an important role in intelligent future, it is accounted that global public cloud market was $272 billion in 2018 which is expected to reach $488.5 billion by 2026. If everything goes well, cloud computing will be applied in more innovative technologies and smart cities in coming future, it will gradually replace traditional datacenter. Perhaps it is the right time for you to move your business to the cloud and take advantages from coming technology revolutions!

* Let us know your comments and suggestions on LayerStack Community.