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The following is the AWS and arm demonstrate production level cloud Electronic Design Automation recommended by recordtrend.com. And this article belongs to the classification: Industry information.
By migrating semiconductor design and verification to the AWS graviton 2 processor based example, arm reduces the risk of cost and scheduling new projects, and increases throughput by 10 times, allowing engineers to focus on innovation. In the future, it plans to reduce the global data center area by at least 45% and reduce local computing by 80%
Beijing – December 11, 2020 – today, Amazon cloud services (AWS) announced that arm, a global leader in semiconductor design and intellectual property development and licensing, will apply AWS cloud services to most of its electronic design automation (EDA) workloads. Arm will take advantage of an example based on AWS graviton2 processor (supported by arm Neover se core) to migrate EDA workload to AWS, leading the transformation path of semiconductor industry. Traditionally, the semiconductor industry uses local data centers for computing intensive tasks such as semiconductor design verification. In order to perform verification more effectively, arm uses cloud computing to simulate real-world computing scenarios, and extends the number of simulations it can run in parallel by taking advantage of AWS’s nearly unlimited storage space and high-performance computing infrastructure. Since moving to the AWS cloud, arm has increased the response time of EDA workflow on AWS by six times. In addition, by running telemetry on AWS (collecting and integrating data from remote sources) and analyzing it, arm generates stronger engineering, business, and operational insight that helps improve workflow efficiency and optimize costs and resources across the company. After the migration to AWS, arm eventually plans to reduce the global data center area by at least 45% and reduce the local computing workload by 80%.
Highly specialized semiconductor devices provide increasingly powerful driving force for everything in our work and life, from mobile phone to data center infrastructure, from medical devices to autonomous driving vehicles. Each chip can contain billions of transistors, which can be reduced to a few nanometers (about 100000 times thinner than a human hair) for optimal performance in minimal space. EDA is one of the key technologies to make this kind of extreme engineering feasible. EDA workflow is very complex, including front-end design, simulation and verification, and increasing back-end workload (timing and power analysis, design rule checking, and other applications ready for production). Traditionally, these highly iterative workflows take months or even years to produce new devices (such as a chip system) and require a lot of computing power. Semiconductor companies operating these workloads locally must constantly balance cost, schedule, and data center resources in order to promote multiple projects at the same time. Therefore, semiconductor companies may face the problem of insufficient computing power, slow down progress or bear the cost of maintaining idle computing power.
By migrating EDA workload to AWS, arm overcomes the constraints of traditional managed EDA workflow, and obtains flexibility through large-scale expansion of computing power, which enables it to run simulation in parallel, simplify telemetry and analysis, reduce iteration time of semiconductor design, increase test cycle, but do not affect the delivery schedule. Arm optimizes EDA workflow by using a variety of specialized Amazon EC2 instance types, reducing cost and time. For example, the company uses an example based on AWS graviton2 to achieve high performance and scalability, enabling more cost-effective operations than running thousands of local servers. Arm uses the AWS compute optimizer service and uses machine learning to recommend the best Amazon EC2 instance type for specific workload, which simplifies the workflow.
In addition to cost advantages, arm also takes advantage of the high performance of AWS graviton2 instance to improve the throughput of engineering workload. Compared with the previous generation of M5 instance based on x86 processor, the throughput per dollar can always be increased by more than 40%. In addition, arm uses the services of AWS partner databricks to develop and run machine learning applications in the cloud. Through the databricks platform running on Amazon EC2, arm can process the data of each step in the engineering workflow, generate feasible insights for the company’s hardware and software teams, and achieve considerable improvement in engineering efficiency.
“By working with AWS, we focus on improving efficiency and maximizing throughput, saving engineers valuable time so they can focus on innovation,” said Rene Haas, President of arm IPG. Now we can run Amazon EC2 instance based on AWS graviton2 processor (supported by arm neoverse), optimize engineering workflow, reduce costs, speed up project progress, and provide strong results to customers faster and more economically than ever before. “
“AWS provides truly resilient high-performance computing, excellent network performance, and scalable storage that is needed for the next generation of EDA workloads,” said Peter de Santis, senior vice president of global infrastructure and customer support at AWS. So we’re happy to work with arm to power EDA workloads that are extremely demanding in performance, using our arm based, high-performance graviton2 processor. The graviton2 processor offers up to 40% price / performance advantages over current X86 based instances. ” More reading: Software: arm planning out! The four-year AWS technology summit, which has occupied hundreds of billions of chips in four years, will set sail in Shanghai. It is expected that more than 50 technical forums and more than 6000 professionals will participate in the summit. Tom cat game family of 40 million will create a “insensible” user experience with AWS cloud services. AWS will distribute financial management services in China to enable customers to use cloud services more economically and efficiently. AWS is released for Amazon Apple MacOS example of EC2 AWS announced that Amazon braket quantum computing service was officially launched. Gartner’s latest report suggested that enterprise customers learn from Amazon’s digital model, Amazon cloud service (AWS) was officially launched in Ningxia and Beijing of China. Amazon sagemaker Netease game chooses AWS global infrastructure to accelerate overseas market development Sagemaker helps Walker AI achieve game content filtering accuracy of 96%. Amazon cloud service (AWS) fully supports smart operation of more than 50 schools of worldwide education group. Amazon re: invent global online summit opens with 43 new services and functions, Softbank acquires arm at a premium of 43% AI I US stocks: mobile processor architecture R & D outsourcing arm – research and analysis report arm: Android smart TV will account for 20% of the shipment in 2012
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