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!

A Speculation of Computing as a Service in the Cloud Computing Stack

Borrowing from Wikipedia, Computing is usually defined as the activity of using and improving computer technology, computer hardware and software. It is clear that both computer hardware and software are important to the development of Computing, but the pace of their development is significant different. Due to the physical limits of the technology, for the past decade, the Chip industry has shifted their focus of developing a single powerful CPU from one single processor to many microprocessor cores. While the development of multi-core processor is underway, there is a new paradigm in Computing (in terms of computer hardware) and that is the GPU. Although the concept is similar (i.e. they are both based on the multi-core architecture), the underlying hardware is fundamentally different and it is this difference which allows them to serve different needs in the application (i.e. some applications are better to be executed on CPU and some are better to be executed on GPU). In order to make the new computer hardware useful, the industry is now looking for better software to take advantage of the new processing powers they offer.

Currently, many applications fail to take advantage of the multi-core architecture because it requires developers to learn a new set of skills in order to make use of them. Programming on the multi-core architecture is challenging for many developers because it requires the developers to think in "parallel" and to handle many pitfalls inherited from parallel programming that are not present in serial programming. Not to mention that developing applications for multi-core CPU is different than multi-core GPU and therefore, it requires them 2X of the effort to take the full advantage of what is available today in the computer hardware. Many universities have recognized the gap between the development of the computer hardware and the computer software and have decided to teach the required skill for programming parallel processors in school and a new textbook has been published recently to support this movement. Personally, I really think this is a good move and I would love to see more universities to engage in this movement. However, I would like to argue that this is not going to help much for the general public unless the movement focuses on solving the real pain point in the Computing world.

The real pain point is that developers should spend most of their development time on delivering business values rather than working with the underlying hardware. Developers are looking for a better way which can facilitate them to develop software on the multi-core architecture without a steep learning curve on the underlying hardware. In fact, software engineers experienced a similar problem in the past and they found a solution for it. The solution is well-known in the Engineering domain and it is called "Virtualization". Virtualization has been used in many places. For example, by virtualizing operating system, a physical machine can be sliced into multiple virtual machines which can then allow to deploy several applications on the same physical machines. I think "Virtualization" can also be applied on the multi-core architecture so that multi-core applications can be developed with "less" pain. It is also a logical and economical way to make use of the available resources. With a group of experts specialized in the multi-core virtualization development, a large population of developers can make use of the multi-core architecture to build high-responsive applications.

One solution available today, that I know of, approaches the concept of multi-core virtualization and it is called Ct Technology. Code can be written once using the development platform provided by Ct Technology, then run in parallel on any of the processors that the Ct Technology Platform supports. The current supported processors are Cell BE, GPUs, and CPUs. I'm hoping to see more of this kind of technology in the future because I believe that it revolutionalizes the computing industry. It abstracts the complexity of the hardware from the application code, freeing the developers to implement applications that matter to the user.

In the future, as blogged in DevCentral, virtualization is becoming the most disruptive infrastructure technology. Especially when Cloud Computing takes off, virtualization will become even more important than one can imagine. Therefore, I'm positive that one day, we will have something called "Computing as a Service" available in the Cloud Computing stack and everyone can access it without knowing what is the underlying computer hardware to execute the actual instructions (be it Cell, GPU or Molecules).

References:

2. My Mental Image of the Technological Landscape for the next 10 Years