Computing as a Service in the Cloud Computing Stack: 2nd Revisit

First of all, I have to admit that I stole this article from one of my posts to the company mailing list. I just modified it to remove confidential information and add more content to align with my previous posts on the same topic.

Apparently, what I proposed previously in the speculation is so realizable that a company actually makes a product about it. :) The company that I'm talking about is "Penguin Computing" . Penguin computing offers "HPC as a Service" that is specifically designed to bring HPC customers to the Cloud. POD is a HPC system in the cloud but NO VIRTUALIZATION technology is used. No virtualization is needed to ensure the performance of their HPC applications is optimal because each customer will have its dedicated PHYSICAL servers to run their HPC application.

You might wonder how this "HPC as a Service" related to my previous posts. Firstly, the "HPC as a Service" allows the HPC customers to run their HPC tasks in the Cloud. Customers are unaware about if their tasks are ran on specific designated resources but they are guaranteed to have the performance they need. Secondly, they provide multi-core virtualization MANUALLY. From the website, it says

"Experts in high-performance computing help setup and optimize the software environment and can help trouble-shoot issues that might occur."

That is if the HPC task doesn't perform as expected, the HPC experts will help the customers to optimize their tasks to run on the specific hardware to take advantage of the hardware resource. Unlike other type of applications that are aimed for high-throughput, HPC tasks are usually long-running algorithms processed in parallel, with the result of one task not dependent on the other tasks. The level of sophistication in this type of task is high and therefore, it has to be fine-tune manually. Although, it doesn't provide the same "virtualization" that I mentioned in the previous post but this is very close to the idea because someone (in this case, the HPC experts) takes care of the messy details about Computing.

Computing as a Service in the Cloud Computing Stack: 1st Revisit

After the previous post about "A Speculation of Computing as a Service in the Cloud Computing Stack", I keep a close observation in the blogosphere to see if anyone in the world has similar ideas on what I proposed in the speculation. Two articles that I found today shed similar lights to the speculation: "The HPC Software Conundrum" and "Engineering Parallel Applications with Tunable Architectures" . The former article says

"... multi-core and streaming-core needs software in a big way. And, there is no sense in bragging about how well the hardware works unless there is an adequate software base to drive the hardware to its intended performance."

The author further lists out a number of solutions that are available today for programmers to use the great hardware and they are OpenMP, CUDA, OpenCL and Ct. However, the author points out that none of these solutions actually tell the programmers how should the code be updated/rewritten using this new tools, "no one size fits all or no silver bullet" as the author would say. He also says

"I still get the feel that it is a kludge of some sort and there should be a way to express what you want to do in a parallel cluster environment using a clear concise standard level of abstraction."

in which I agree with him. There is a need for a layer of abstraction that takes care of the hardware, be it SMP multi-core with or without GPU architecture. The layer of abstraction should be intelligent enough to make use of all the available hardware in the machine to improve the utilization.

The second article suggests a new approach to address the difficulty in adapting a serial program to a parallel program on the new hardware architecture. The new approach will automate the architecture adaptation of parallel programs and uses an auto-tuner to find the best-performing architectural choice for a given machine by introducing a new architecture description language based on parallel patterns and a framework for expressing architecture variants in a generic way. This is a step toward multi-core virtualization.

I wish to see more contributions on the software side to bring the programmers to this multi-core era!