Are they significantly cheaper per GHz*core? If so, how hard is it to make use of that power, will a simple recompile work?
> 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.
> provide up to 40% better price performance over comparable current generation x86-based instances1 for a wide variety of workloads,
From what I read, it's not terribly hard to tell your compiler to compile for a particular instruction set, you just need to do it. Cost savings and better performance are great incentives, as well as Apple moving their Mac platform to it will drive more market share for developers to take the time to recompile.
Edit: Forgot to add the source of those quotes: https://aws.amazon.com/ec2/graviton/
Once it is fixed you are fine. Most of the big programs you might use are already fixed. Some languages give you gaurentees that make it just work.
So e.g., on x86 if you store to A then store to B, then if another core sees the store to B it is guaranteed to see the store to A as well. This guarantee does not exist on ARM.
But on x86, many of these things don't matter, if I understand correctly.
Two threads reading and writing to the same memory area do not necessarily give problems. In fact, many software is built to exploit several facts about how memory accesses work with respect each other.
ARM processors give very few guarantees, so code has to workaround that.
It's good to be skeptical. I always encourage folks do experiments using their own trusted methodology. I believe that the methodology that engineering used to support this overall benefit claim (40% price/performance improvement) is sound. It is not the "benchmarketing" that I personally find troubling in industry.
But We can't measure power consumption/heat, possibly noisy neighbor exists while benchmarking, and can't know real price for cloud instance. I don't blame but it's difficult to comparing a hardware.
In the context of AWS.
They are cheaper per some / specific workload* on AWS.
Especially when ARM Graviton 2's vCPU on AWS are actual CPU core while Intel / AMD instances are CPU thread.
And in general AWS offers the G2 instances with the same vCPU core at 20% discount compared to AMD / Intel instances.
Thank you for that information. Is there a reference that documents this somewhere?
Each vCPU is a thread of either an Intel Xeon core or an AMD EPYC core, except for M6g instances, A1 instances, T2 instances, and m3.medium.
Each vCPU on M6g instances is a core of the AWS Graviton2 processor.
Each vCPU on A1 instances is a core of an AWS Graviton Processor.
Of course different cpus can do different amounts of work per amount of electricity used, but arm generally works out better on a watt per unit of work basis.