NEW ARM-Based Amazon Graviton CPU

-
It’s only been a few weeks since Amazon announced that it would offer AMD Epyc servers as an option for Amazon Web Services (AWS). Now the company is announcing a new type of hardware platform for its just-created A1 instances — the Amazon Graviton processor.



The Graviton CPU


Here’s what we know about the Graviton to date. It’s based on the Cortex-A72, with a maximum clock speed of 2.3GHz. AWS VP James Hamilton writes:
These new instances feature up to 45% lower costs and will join the 170 different instance types supported by AWS, ranging from the Intel-based z1d instances which deliver a sustained all core frequency of 4.0 GHz, a 12 TB memory instance, the F1 instance family with up to 8 Field Programmable Gate Arrays, P3 instances with NVIDIA Tesla V100 GPUs, and the new M5a and R5a instances with AMD EPYC Processors. No other cloud offering even comes close.



Almost an AMD Win


It’s easy to forget, but once upon a time, AMD was making a huge bet on ARM CPUs, not x86. When AMD announced its K12 CPU back in 2015, it chose to hand the “K” moniker — a label previously reserved for x86 chips — to a future ARM core. K12, we were told, would share extensive resources and development strategy with Zen. There were plans for an ambitious joint x86-ARM platform, dubbed Project Skybridge. According to The Register, Amazon and AMD were working closely together in 2015, until “AMD failed at meeting all the performance milestones Amazon set out.”
It’s not clear what milestones, precisely, AMD failed to meet — but we could pick from several. The company’s Project Skybridge was abruptly canceled (we speculated at the time that GF’s manufacturing woes could have been part of the problem), and its Cortex-A57 CPU, the Opteron A1100, was announced in 2014 but didn’t actually ship until 2016. If we had to guess, we’d guess the problems were with the A1100. Back then, AMD explained that part of the reason the A1100 was held back was that the infrastructure for ARM server deployments wasn’t as solid as it needed to be and that more work had to be done bringing the software stack up to snuff. That may well have been entirely true — ARM servers have taken years longer to come to market than anyone originally expected — but Amazon apparently wasn’t willing to wait. The firm dropped AMD and bought Annapurna Labs to perform its design work.
This may also explain why AMD shelved K12. Lisa Su has focused on semi-custom parts, and serving as a dedicated provider for Amazon’s ARM business could definitely have fit that target. In this telling, either Skybridge, Seattle, or both were trial balloons to demonstrate that AMD could bring ARM IP to market before launching a new custom part based on some of the same architectural building blocks as its x86 CPU. When AMD lost the Amazon opportunity, it may have moved to shelve its ARM design — and that, in turn, may have been part of why Jim Keller left the company when he did. All of this is speculation, to be clear — it just fits the timeline reasonably well.
Regardless of how things turned out with AMD, this is the first time we’ve seen ARM servers deployed in cloud instances and a significant step forward for the ecosystem for that reason alone.




AWS Graviton processors are custom-built by Amazon Web Services using 64-bit Arm Neoverse cores to deliver the best price performance for your cloud workloads running in Amazon EC2. Amazon EC2 provides the broadest and deepest portfolio of compute instances, including many that are powered by latest-generation Intel and AMD processors. AWS Graviton processors add even more choice to help customers optimize performance and cost for their workloads.
The first-generation AWS Graviton processors power Amazon EC2 A1 instances, the first ever Arm-based instances on AWS. These instances deliver significant cost savings over other general-purpose instances for scale-out applications such as web servers, containerized microservices, data/log processing, and other workloads that can run on smaller cores and fit within the available memory footprint.
AWS Graviton2 processors deliver a major leap in performance and capabilities over first-generation AWS Graviton processors. They power Amazon EC2 M6g, C6g, and R6g instances that provide up to 40% better price performance over comparable current generation instances1 for a wide variety of workloads, including application servers, micro-services, high-performance computing, electronic design automation, gaming, open-source databases, and in-memory caches. The AWS Graviton2 processors also provide enhanced performance for video encoding workloads, hardware acceleration for compression workloads, and support for CPU-based machine learning inference. They deliver 7x performance, 4x the number of compute cores, 2x larger caches, and 5x faster memory compared to the first-generation Graviton processors.


Benefits

Best price performance for a broad spectrum of workloads

AWS Graviton2-based general-purpose (M6g), compute-optimized (C6g), and memory-optimized (R6g) EC2 instances deliver up to 40% better price performance over comparable current generation instances1 for a broad spectrum of workloads such as application servers, micro-services, video encoding, high-performance computing, electronic design automation, compression, gaming, open-source databases, in-memory caches, and CPU-based machine learning inference. M6g instances are now available in preview. These instances, along with C6g and R6g instances and M6gd, C6gd, and R6gd variants with local NVMe-based SSD storage will be generally available soon.

Extensive ecosystem support

AWS Graviton2 processors, based on the 64-bit Arm architecture, are supported by several popular Linux operating systems including Amazon Linux 2, Red Hat Enterprise Linux, SUSE Linux Enterprise Server, and Ubuntu. Many popular applications and services from AWS and Independent Software Vendors also support AWS Graviton2-based instances, including Amazon ECS, Amazon EKS, Amazon CodeBuild, Amazon CodeCommit, Amazon CodePipeline, Amazon CodeDeploy, Amazon CloudWatch, Docker Desktop and Enterprise Engine, Rancher k3s, NGINX, Datadog, CrowdStrike, and Jenkins. Arm developers can also leverage this ecosystem to build applications natively in the cloud, thereby eliminating the need for emulation and cross-compilation, which are error prone and time consuming.

Enhanced security for cloud applications

Developers building applications for the cloud rely on cloud infrastructure for security, speed and optimal resource footprint. AWS Graviton2 processors feature key capabilities that enables developers to run cloud native applications securely, and at scale, including always-on 256-bit DRAM encryption and 50% faster per core encryption performance compared to first-generation AWS Graviton. Graviton2 powered instances are built on the Nitro System that features the Nitro security chip with dedicated hardware and software for security functions, and support encrypted EBS storage volumes by default.


Comments

Post a Comment

Popular posts from this blog

Difficulty in Learning Programming Languages? Follow these guided steps

-
Image
img .. Learning a new Programming Language is always very hard but it is not as difficult as learners make it. While it always involves some kind of frustration to learn a  new Programming Language in the starting but as time passes by and you gain mastery over a language things become very easy and interesting for you. Many of the learners quits their first programming language after their some unsuccessful attempts and make a diversion in their career. This is for the reason I decided to write an article for anyone who is on the difficult terrain of learning a programming language and want some guide to help him out in tackling the challenges faced in Programming. Well, I have come her for you with some of the most useful and guided steps that you should and must follow while learning any Programming Languages. Whether you are learning C,Java, Python, Scala or any Programming Language, keep these guided steps with you and elevate to the greater heights of programming....
Read more

WHAT IS INSERTION SORT ?

-
Image
INSERTION SORT  I nsertion sort is a very simple sorting algorithm in which the sorted array (or list) is built one element at a time. We all are familiar with this technique of sorting, as we usually use it for ordering a deck of cards while playing bridge. The main idea behind insertion sort is that it inserts each item into its proper place in the final list. To save memory, most implementations of the insertion sort algorithm work by moving the current data element past the already sorted values and repeatedly interchanging it with the preceding value until it is in its correct place. Insertion sort is less efficient as compared to other more advanced algorithms such as quick sort, heap sort, and merge so Technique    Insertion sort works as follows:  The array of values to be sorted is divided into two sets. One that stores sorted values and another that contains unsorted values.   The sorting algorithm will proceed unti...
Read more

Why coding and programming are in trend and what's the difference?

-
Image
Because of An Hour of Code (often giving people the strange delusion that he or she can earn a higher wage by throwing symbols at a screen without understanding what, exactly they're doing. It will benefit you in a positive sense (not just a new fast food monkey throwing symbols at a screen), if you can dedicate more than an hour of code a day or week, and it interests you, and you keep at it and keep learning more (evolve with technology, and understand how to do programming for different technologies, how they interact, and how to solve problems in an efficient manner). What's the best thing about coding/programming? Programming is like writing a story. Except for the characters and plotlines, you write to exist in the truest sense. An app or data analysis tool doesn't have to leap off a page or be confined to the imagination, or the whiteboard. The code can control and do real things. Code is magic and fantastic. To an outsider (or someone programming b...
Read more