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Leveraging Cloud Computing in CAE Product Development Environments (Part II)

admin — Tue, 29 Mar 2011 04:20:35 +0000

Client Risks and Limitations

Security Concerns

Will data be secure in cloud based product development?

While it is important to that vendors are selected with care, cloud based processing and storage of sensitive data has become common within Fortune 500 companies.[1] Standards and certifications exist to ensure that no unauthorized access occurs and sensitive data is kept secure.[i]

Scalability Concerns

How scalable is computational processing?

Disciplinary solvers for specific engineering disciplines will always have natural limitations to scalability. However, many current processes are not yet approaching diminishing returns and a variety of opportunities exist to exploit coarse-grain and medium-grain parallelization immediately. Furthermore, integration across functional disciplines will provide further opportunities for concurrent processing.

Integration Concerns

How will disciplinary software be integrated?

Software providers do need to make appropriate adjustments to fully integrate with cloud based platforms. Current vendors provide various levels of integration opportunities through API interfaces. Incentives are aligned for software vendors to continue the development of these interfaces to integrate closely into cloud based platforms. Additionally, leading CAE vendors indicate a strong willingness to participate in further development opportunities.

Immediate Opportunities

The following opportunities can be explored to move toward a cloud based product development vision. Each opportunity can be examined in the form of a pilot project and be implemented in a low risk controlled environment within which benchmarking tests can be completed to verify and quantify the extent to which clients can benefit from cloud based product development.

Cloud Based High-Performance Computing (complementary to existing services)

Cloud based HPC will allow clients to immediately start capturing the benefits of additional computing resources in a controlled environment. Benchmarking tests for functional disciplines will allow accurate quantification of the benefits that cloud based high-performance computing can provide within various product development environment verticals. Integrating third-party cloud computing services with the existing CAE tool suite will allow clients to immediately access additional computing power when needed. Providing these capabilities will eliminate barriers to entry for both existing and new clients to experience the benefits of cloud based HPC.

Virtualization experts[ii]^,[iii],[iv] and case studies[2]^,[v],[vi] have verified that cloud based high-performance computing is beneficial and viable from both an academic and practical perspective. Leading automotive and aerospace clients have demonstrated a strong interest to evaluate cloud based HPC opportunities.

Cloud Based Integration Platform (complementary to cloud based HPC)

Developing a cloud based platform to integrate disciplinary software and other third-party product development tools provides the opportunity for clients to explore the product performance benefits that can be gained from integration across multiple functional silos within an organization regardless of which software providers are used. Benchmarking tests with clients will demonstrate the level at which current software and third-party tools can be integrated through using existing application programming interfaces (API) while using cloud based HPC for computation power.

Existing software integration platforms lack both cloud based capabilities and a deep enough integration with third-party independent software vendors to provide the full benefits that an integrated platform could provide. Developer tools and customized implementation of a cloud based integration platform will be able to provide a deeper integration into third-party software and eliminate the computational bottlenecks that make leading software integration platforms impractical for large-scale production product development environments.

Independent software vendors (ISV) and clients in relevant industry verticals have both shown interest to participate in and deploy cloud based integration platforms. There are numerous incentives and benefits to CAE software providers, third-party ISV’s, and clients to participate in a cloud based product development platform.

A Call to Action

Moving toward cloud based product development environment will provide numerous benefits to the product development processes of clients that will reduce development timelines, improve product performance, and reduce costs. Cloud computing technology has matured far enough that the benefits far outweigh the risks associated with the proposed developments. Leading software providers and industry pundits agree that the transition to cloud based computing and smart integration of software tools will be two main sources of value creation in computer aided engineering tools in the short to medium term.[vii]

“[Organizations] run [cloud based HPC] applications such as mapping genomes for scientific research, simulating aerospace and automotive designs for engineering activities, mining data for business intelligence and many other use cases.”[viii] Recent case studies have addressed the risks and demonstrated magnitudes of improvements on performance and drastic reductions in cost which easily make the case for cloud based HPC on a standalone basis, exclusive of the significant additional potential benefits from integration across functional disciplines in a cloud based product development platform.

A proactive investment to explore the aforementioned benefits in cloud based product development is likely to provide invaluable returns for clients in the form of sustainable competitive advantage over the longer term. With swift action, clients will quickly be able to start leveraging the benefits of cloud computing technology, reducing the time and cost to innovate and improving the performance of their products.

[1] Salesforce.com illustrates the willingness of leading companies to trust the security of cloud based services with some of their most sensitive data

[2]Josh Simons mentions (at ISC Cloud ’10) a successful case study in financial services where significant benefits were realized from moving to cloud based HPC across multiple disciplines, http://communities.vmware.com/docs/DOC-13947

[i] “Amazon Web Services Overview of Security Processes”, Amazon.com, http://media.amazonwebservices.com/pdf/AWS_Security_Whitepaper.pdf, August 2010

[ii] “Why Virtualize HPC?”, Josh Simons, http://communities.vmware.com/community/cto/high-performance/blog/2010/08/25/why-virtualize-hpc, accessed February 2011

[iii] “Virtualization for High Performance Computing”, Mark F. Mergen, Volkmar Uhlig, Orran Krieger, Jimi Xenidis, IBM Research Center, ACM SIGOPS Operating Systems Review, Volume 40 Issue 2, April 2006

[iv] “A case for high performance computing with virtual machines”, Wei Huangy, Jiuxing Liuz, Bulent Abaliz, Dhabaleswar K. Panday, Ohio State University, ICS ’06 Proceedings of the 20th annual international conference on Supercomputing

[v] NASA JPL Case Study, “AWS Case Study: NASA Jet Propulsion Lab’s Desert Research and Training Studies”, http://aws.amazon.com/solutions/case-studies/nasa-jpl/

[vi] Cycle Computing Case Study, “AWS Case Study: Cycle Computing and Varian”, http://aws.amazon.com/solutions/case-studies/cyclecomputing/

[vii] “Smart Computing Solutions Are On The Rise”, Forrester Research, January 2011

[viii] “HPC Applications”, Amazon.com, http://aws.amazon.com/ec2/hpc-applications/, accessed February 2011

This post appeared on Vludo’s blog a company focused on developing the platform for the next generation of product development using cloud computing and big data tools.

Leveraging Cloud Computing in CAE Product Development Environments (Part I)

admin — Wed, 23 Mar 2011 04:58:01 +0000

Cloud computing offers significant benefits to the development of CAE engineered products including the reduction of development timelines, improvement of product performance, and significant reductions in overall development cost. The complete benefits of cloud computing in product development environments for clients can only be realized with full participation and understanding among all stakeholders involved and careful implementation within a firms IT infrastructure. While the full benefits of cloud based product development will only be realized with a significant transition of software and databases, partial transitions in high-performance computing and linking of interdependent disciplinary software and databases can already provide significant returns in the short term.

Client first movers in cloud based product development would likely gain a significant sustainable competitive advantage over competitors in leading technology development in this area. The following enumerates potential benefits for both engineering and management from the transition to cloud based product development, along with potential risks and limitations.

Client Engineering Benefits

Reduced development timelines

Cloud based high-performance computing provides access to a virtually unlimited amount of computing power immediately as needed, eliminating computational bottlenecks
Dynamic scaling of computing resources provides the ability to always use appropriate compute resources for all computational workloads
Integrating data and software across functional silos reduces the number of iterations needed to converge on a final design

Improved product performance

Cloud based product development allows for a broad design of experiments on the same timeline as a single iteration, significantly increasing the probability of improved and optimal product design
Linking disciplinary processes provides opportunities for improved understanding and communication across functional silos resulting better optimization of products through capturing interdependencies and tradeoffs in product design
Shared dynamic design databases and linkages across functional software data can eliminate commonly occurring errors and wasted effort in working with non-current or incorrect data

Client Management Benefits

Cost Reductions

Cloud based product development reduces time spent on repeated sequential iterations to achieve design convergence and allows engineers focus on higher value added activities
Capital expenditures for grid computing can be reduced and converted to flexible hourly operating costs matching cyclical development cycles
Pay-per-use licensing models[1] allow for more direct association between costs and actual value created by product development software

Visibility and Control

Increased oversight, transparency, visibility, and control of the product development process through common platform usage across disciplinary teams
Increased ability to measure progress with clear metrics and manage local and global product development teams

[1] Leading computer aided engineering (CAE) software vendors indicate these are not only viable, but likely as product development software moves into the cloud

This post appeared on Vludo’s blog a company focused on developing the platform for the next generation of product development using cloud computing and big data tools.

Creating Mountains of Technical Debt in Lean Startups

admin — Mon, 21 Mar 2011 05:13:39 +0000

This post originally appeared in Launching Technology Ventures a Harvard Business School MBA elective course that examines lean startup management practices.

Lean methodology values employing minimal effort to get to the next milestone. Lean principles have a short-term focus to test hypotheses, which is quite rational considering that once a hypothesis is disproven you haven’t wasted any time in further wasted effort. Customer development methodologies also encourage similar principles, ensuring a deep understanding of the customer and the market before embarking on the development of an expensive product that nobody wants to buy. These lean principles and culture will work great in optimizing the path to get initial traction, but could wreak havoc on further development of the product causing avoidable risks down the line.

Creating technical debt through minimizing waste

Specifically in software development, lean product development can result in significant technical debt. To be sure, technical debt refers to the costs associated with hasty software development resulting in neglecting architecture, incomplete testing, and incomplete documentation. Subsequently, once a product has accumulated technical debt, further development work contains interest payments on this debt in the form of building on code that still needs further work to truly be complete. In the future, this debt can be paid off through rewriting the code in the right architecture as intended, completing all the testing necessary, and completing documentation. Acquiring technical debt, in fact, is often a direct result from applying lean principles, since activities that do not add immediate value to achieving the next milestone in a product release should be considered waste.

Vicious cycles of technical debt

The issue of technical debt accumulation is further compounded by the fact that once technical debt has been accumulated, cost-benefit analysis will often show that paying off the debt creates value in the long term, but destroys value in the short term – thus a bad decision if you are choosing the most efficient lean path to the next milestone. This vicious cycle of technical debt accumulation can result in large amounts of increasing debt overhang, causing significant amounts of interest payments that significantly hinder and potentially stall further development. The vicious technical debt cycle is analogous to taking out increasingly higher rate credit cards to pay off previous debt accumulated; you keep buying yourself a short term lifeline at an increasingly higher long term penalty.

Symptoms of technical debt are hard to identify

While a great developer with intricate knowledge of the code can provide a decent estimate of technical debt, this debt is often hidden and unknown to higher management. The symptoms of technical debt are very hard to identify. A development cycle with large technical debt interest payments results in development delays that often can’t be attributed to anything in specific, typically unfairly blamed on the miscalculation of estimated development timelines. Subsequent decisions made based on a misunderstanding of technical debt situations can lead a startup astray – resulting in anything from slight misallocation of resources to cutting off potentially profitable product lines. In situations where technical debt is the root cause of development delays, misinterpretation by management can result in severely misguided decisions.

How to really stay lean

Using lean methodology as a guide, product development timelines and decisions should be made balancing the optimal short term solutions with an awareness of the long term consequences. There is nothing wrong with accumulating technical debt, in fact similar to financial situations, acquiring some debt to attain certain milestones more quickly can certainly result in value creation. But be mindful of the longer term risks involved and addicting qualities of debt, a vicious cycle of technical debt can create a house of cards that will sooner or later come crashing down. Early investments in good software architecture, testing, and documentation create higher cost and minimal benefit in the short term, but can pay huge dividends in the long term.

Some tips on how to avoid acquiring mountains of technical debt in a lean startup:

Ensure management has a clear understanding of the level of technical debt
Balance the short term needs for technical debt creation, with the longer term benefits of paying it off
Understand the large shadow cast on software development by architecture, testing, and documentation

Lean Startups: The Most Efficient Path To Non-Differentiation

admin — Mon, 14 Mar 2011 00:32:47 +0000

This post originally appeared in Launching Technology Ventures a Harvard Business School MBA elective course that examines lean startup management practices.

In a hypothesis-driven lean start-up environment, lean theory recommends maximizing your learning from customers while minimizing effort. While the theory sounds great, if lean startups follow lean principles blindly it could lead to unintentionally bland results. More specifically, if the product vision is truly inspired, lean approaches can drive the development path away from a disruptive new solution and gravitate more toward incremental improvements upon existing products.

Lean methodologies can stifle innovation

Lean principles originated in the manufacturing environment to help reduce waste and focus on value-added activities. In manufacturing environments however, lean principles are typically only implemented once both the production processes and product are very well defined. In contrast, in the R&D lab lean principles can inhibit collaboration, creativity and innovation. To be sure, there are certainly ways to improve the efficiency of the innovation process. In fact, IDEO has developed their business around ways to achieve this in a repeated fashion. In an uncertain innovative environment, the value that certain activities bring to the final solution can often only be identified as such in hindsight. In a start-up, just like in an R&D lab, the product is still not yet fully defined and structured processes can limit the creativity of innovation and breadth of outcomes. Additionally, iterative continuous improvement principles can severely limit the final product results from lean start-ups to incremental improvements. If the lean startup methodology is implemented without careful thought, the original vision of the startup will likely be discarded pre-maturely.

Customer feedback can be misleading

A truly disruptive product solves a problem in a creative novel way, and often requires new customer behaviors. If a customer needs to behave differently for your product to work, customer-centric development and feedback needs to be approached with care. Customer feedback and behaviors may be skewed toward experiences with existing products. Thus early adopter customers can give misleading feedback, and cause the product development path to stray away from the original vision – before this vision has even been appropriately tested. An ideal visionary customer can perhaps piece together where you are trying to go with your product, but this can be very unreliable. Real valuable customer feedback comes from a completed product, not half of a prototype and some hand waving.

Splitting interdependent hypotheses can lead to false results

Disruptive products often have a whole hypothesis composed of a group of sub-hypotheses that are interdependent on each other. Testing these hypotheses independently can lead to both false-positives and false-negatives. Just because you couldn’t sell the peanut butter or jelly sandwiches independently, doesn’t mean the peanut butter and jelly sandwich isn’t a great snack. Customer feedback used to test a hypothesis only becomes valuable with a product that is able to test your whole hypothesis. Thus if maximum learning really only occurs with all the pieces of a complex product pieced together, then your minimum viable product is really just your first whole product release, just like in traditional product development.

Lean startup methodology is a helpful guide, but not gospel

Lean startup methodology provides great advice on ways to iterate quickly and get customers involved in startup product development. Ultimately I do believe Steve Blank’s book (Four Steps to the Epiphany) and Eric Ries’ lean startup methodology are extremely effective as a guide – but should be interpreted with care.

Some tips to help avoid these potential lean methodology pitfalls:

Don’t stifle early innovation by over-applying lean principles
Test interdependent hypotheses with whole products
Keep a strong vision and filter customer feedback