Zara  Bryant

Zara Bryant

1602899731

Faster and Lighter Model Inference with ONNX Runtime from Cloud to Client

ONNX Runtime is a high-performance inferencing and training engine for machine learning models. This show focuses on ONNX Runtime for model inference. ONNX Runtime has been widely adopted by a variety of Microsoft products including Bing, Office 365 and Azure Cognitive Services, achieving an average of 2.9x inference speedup. Now we are glad to introduce ONNX Runtime quantization and ONNX Runtime mobile for further accelerating model inference with even smaller model size and runtime size. ONNX Runtime keeps evolving not only for cloud-based inference but also for on-device inference.

Jump To:
[01:02] ONNX and ONNX Runtime overview https://aka.ms/AIShow/ONNXRuntimeGH
[02:26] model operationalization with ONNX Runtime
[04:04] ONNX Runtime adoption
[05:07] ONNX Runtime INT8 quantization for model size reduction and inference speedup
[09:46] Demo of ONNX Runtime INT8 quantization
[16:00] ONNX Runtime mobile for runtime size reduction

Learn More:
ONNX Runtime https://aka.ms/AIShow/ONNXRuntimeGH
Faster and smaller quantized NLP with Hugging Face and ONNX Runtime https://aka.ms/AIShow/QuantizedNLP
ONNX Runtime for Mobile Platforms https://aka.ms/AIShow/RuntimeforMobilePlatforms
ONNX Runtime Inference on Azure Machine Learning https://aka.ms/AIShow/RuntimeInferenceonAML

#cloud #programming #developer

What is GEEK

Buddha Community

Faster and Lighter Model Inference with ONNX Runtime from Cloud to Client
Adaline  Kulas

Adaline Kulas

1594162500

Multi-cloud Spending: 8 Tips To Lower Cost

A multi-cloud approach is nothing but leveraging two or more cloud platforms for meeting the various business requirements of an enterprise. The multi-cloud IT environment incorporates different clouds from multiple vendors and negates the dependence on a single public cloud service provider. Thus enterprises can choose specific services from multiple public clouds and reap the benefits of each.

Given its affordability and agility, most enterprises opt for a multi-cloud approach in cloud computing now. A 2018 survey on the public cloud services market points out that 81% of the respondents use services from two or more providers. Subsequently, the cloud computing services market has reported incredible growth in recent times. The worldwide public cloud services market is all set to reach $500 billion in the next four years, according to IDC.

By choosing multi-cloud solutions strategically, enterprises can optimize the benefits of cloud computing and aim for some key competitive advantages. They can avoid the lengthy and cumbersome processes involved in buying, installing and testing high-priced systems. The IaaS and PaaS solutions have become a windfall for the enterprise’s budget as it does not incur huge up-front capital expenditure.

However, cost optimization is still a challenge while facilitating a multi-cloud environment and a large number of enterprises end up overpaying with or without realizing it. The below-mentioned tips would help you ensure the money is spent wisely on cloud computing services.

  • Deactivate underused or unattached resources

Most organizations tend to get wrong with simple things which turn out to be the root cause for needless spending and resource wastage. The first step to cost optimization in your cloud strategy is to identify underutilized resources that you have been paying for.

Enterprises often continue to pay for resources that have been purchased earlier but are no longer useful. Identifying such unused and unattached resources and deactivating it on a regular basis brings you one step closer to cost optimization. If needed, you can deploy automated cloud management tools that are largely helpful in providing the analytics needed to optimize the cloud spending and cut costs on an ongoing basis.

  • Figure out idle instances

Another key cost optimization strategy is to identify the idle computing instances and consolidate them into fewer instances. An idle computing instance may require a CPU utilization level of 1-5%, but you may be billed by the service provider for 100% for the same instance.

Every enterprise will have such non-production instances that constitute unnecessary storage space and lead to overpaying. Re-evaluating your resource allocations regularly and removing unnecessary storage may help you save money significantly. Resource allocation is not only a matter of CPU and memory but also it is linked to the storage, network, and various other factors.

  • Deploy monitoring mechanisms

The key to efficient cost reduction in cloud computing technology lies in proactive monitoring. A comprehensive view of the cloud usage helps enterprises to monitor and minimize unnecessary spending. You can make use of various mechanisms for monitoring computing demand.

For instance, you can use a heatmap to understand the highs and lows in computing visually. This heat map indicates the start and stop times which in turn lead to reduced costs. You can also deploy automated tools that help organizations to schedule instances to start and stop. By following a heatmap, you can understand whether it is safe to shut down servers on holidays or weekends.

#cloud computing services #all #hybrid cloud #cloud #multi-cloud strategy #cloud spend #multi-cloud spending #multi cloud adoption #why multi cloud #multi cloud trends #multi cloud companies #multi cloud research #multi cloud market

Adaline  Kulas

Adaline Kulas

1594166040

What are the benefits of cloud migration? Reasons you should migrate

The moving of applications, databases and other business elements from the local server to the cloud server called cloud migration. This article will deal with migration techniques, requirement and the benefits of cloud migration.

In simple terms, moving from local to the public cloud server is called cloud migration. Gartner says 17.5% revenue growth as promised in cloud migration and also has a forecast for 2022 as shown in the following image.

#cloud computing services #cloud migration #all #cloud #cloud migration strategy #enterprise cloud migration strategy #business benefits of cloud migration #key benefits of cloud migration #benefits of cloud migration #types of cloud migration

Thurman  Mills

Thurman Mills

1620754080

Top 4 Cloud Computing Models Explained

Whether you are a business owner looking to shift your current on-premise infrastructure to the cloud, or a student who wants to start learning cloud computing, the first step is knowing about cloud computing models. The three models that you will come across are – IaaS, PaaS, and SaaS. These models have many distinct features. You can avail of these cloud services over the Internet easily.

Cloud Computing Models

1. IaaS (Infrastructure as a Service)

IaaS is one of the most important cloud computing models that provides you with networking hardware over the Internet. These resources are provided to you through virtualization. This means that you can log in to an IaaS platform to use virtual machines (VM) to install an OS or software and run databases. This VM can work as a virtual data center.

#cloud computing #cloud computing models #cloud models #cloud

Zara  Bryant

Zara Bryant

1602899731

Faster and Lighter Model Inference with ONNX Runtime from Cloud to Client

ONNX Runtime is a high-performance inferencing and training engine for machine learning models. This show focuses on ONNX Runtime for model inference. ONNX Runtime has been widely adopted by a variety of Microsoft products including Bing, Office 365 and Azure Cognitive Services, achieving an average of 2.9x inference speedup. Now we are glad to introduce ONNX Runtime quantization and ONNX Runtime mobile for further accelerating model inference with even smaller model size and runtime size. ONNX Runtime keeps evolving not only for cloud-based inference but also for on-device inference.

Jump To:
[01:02] ONNX and ONNX Runtime overview https://aka.ms/AIShow/ONNXRuntimeGH
[02:26] model operationalization with ONNX Runtime
[04:04] ONNX Runtime adoption
[05:07] ONNX Runtime INT8 quantization for model size reduction and inference speedup
[09:46] Demo of ONNX Runtime INT8 quantization
[16:00] ONNX Runtime mobile for runtime size reduction

Learn More:
ONNX Runtime https://aka.ms/AIShow/ONNXRuntimeGH
Faster and smaller quantized NLP with Hugging Face and ONNX Runtime https://aka.ms/AIShow/QuantizedNLP
ONNX Runtime for Mobile Platforms https://aka.ms/AIShow/RuntimeforMobilePlatforms
ONNX Runtime Inference on Azure Machine Learning https://aka.ms/AIShow/RuntimeInferenceonAML

#cloud #programming #developer

Thurman  Mills

Thurman Mills

1620721560

Cloud Deployment Models: Types of Models & Applications

What is Cloud Computing?

Cloud computing has emerged significantly over the past decade. The cloud deployment models essentially refer to how the servers are deployed and provisioned over the internet so that they can be accessed remotely by individuals and companies, without the need to configure them.

Why is Cloud Computing Becoming Popular?

Utilizing cloud deployment models provides multiple benefits like boosting productivity and providing a competitive advantage to organizations. With the growing popularity of cloud computing models, organizations are coming up with a variety of cloud deployment strategies designed to address specific infrastructure challenges that organizations face and the cloud computing solutions that they desire.

The different deployment strategies offer different levels of flexibility, cost-control, and data management within enterprises.

Cloud computing service models make it possible for companies to deploy and render several services, classified according to the roles, service providers, and user companies.

#cloud computing #cloud #cloud deployment #cloud deployment models