Top White Papers

The business case for earlier software defect detection and compliance

Regardless of the industry your business operates in, software is likely all around it. Software powers our cars, airplanes, and even the medical devices we rely on to diagnose and treat illness...

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Can connected cars be secure cars?

There is growing awareness and concern over software security in the automobile industry. Learn about the challenges facing the industry today and what can be done to boost software security.

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Software security begins with flaw-free, standards-compliant code

Research shows that improving code security starts with developers.

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Four strategies to reduce your open source risk

Try to think of a single system in the world that hasn’t been touched by open source software...

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White Papers

Using JMSL in Hadoop MapReduce applications

The excitement around big data is the expectation of better results and new insights as we take more accurate measurements of our world. Among the many important considerations to help reach this potential is deciding how to perform efficient mathematical and statistical analysis on the data when traditional storage methods are no longer feasible, reasonable, or possible. The answer is to combine Hadoop MapReduce with JMSL Numerical Libraries.

Learn more by walking through a few technical examples and code of how to use JMSL Numerical Libraries in Hadoop MapReduce applications.

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Top 3 strategies to reduce risk in automotive / in-vehicle software development

Developing in-vehicle embedded applications is a safety, security, and quality challenge. Given that cars and trucks are increasingly connected to each other and to the devices around them, it’s becoming harder and harder to ensure that software is functional and free from risk. Development teams, especially the managers who are ultimately responsible, face incredible challenges when building such applications, and are learning that team members need to do more than just catch code defects during verification and validation testing. The new imperative: Identify and address security and compliance concerns earlier in the lifecycle, all while delivering innovative and differentiating features.

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Rogue Wave tools and libraries for big data

Big data applications are among the fastest-growing and demanding in the business and research communities, encompassing a range of workloads in real-time analytics, data mining, complex event processing, MapReduce applications, and visualization. Besides the need for high performance, big data applications must also handle data complexity, varying data properties, and optimizing storage capacity.

In this report, senior analyst Michael Feldman from Intersect360 Research discusses these challenges in the big data developer market and presents an analysis of how unique tools and libraries from Rogue Wave Software increase developer productivity and reduce deployment and maintenance costs.

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Rogue Wave tools and libraries for financial services

Financial services is the second largest vertical market of high performance computing, including high-frequency trading, risk management, securities and derivatives pricing, and economic analytics. With increased competition, a growing skills gap, and stronger regulations, it's more challenging than ever to deliver applications that meet demanding performance requirements.

In this report, senior analyst Michael Feldman from Intersect360 Research discusses the current financial services developer market and presents an analysis of how unique tools and libraries from Rogue Wave Software increase developer productivity and reduce deployment and maintenance costs.

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Software as a process

Today’s software products are the result of many suppliers, vendors, open source repositories, and legacy code coming together in a mix of different processes, standards, and cultures. Each input offers a chance to introduce safety, security, or performance-related errors.

This paper explains the challenges of this polyglot environment and how strategies and tools proven in a number of industries can be applied to your organization to reduce defects, meet requirements, and minimize costs.

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Coding to standards and quality: supply-chain application development

The monolithic codebase is dead. Modern applications are built of code from a variety of sources including employees, partners, and contractors from different geographies, with different skill levels, and working on a number of platforms. Application development is a supply chain, with dependencies supported by a network of systems ranging from greenfield development to legacy integrations, and utilizing a patchwork of code from custom, open-source, and commercial third-party sources. Ensuring consistency, security, and standards in such an environment can be challenging, but is essential for maintaining reputation, relationships, and customers.

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Time series analysis Auto Arima

Time series analysis is used by many industries in order to extract meaningful statistics, characteristics, and insights. Businesses use time series to improve business performance or mitigate risk in applications such as finance, weather prediction, cell tower capacity planning, pattern recognition, signal processing, and engineering.

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TotalView CUDA

CUDA introduces developers to a number of new concepts (such as kernels, streams, warps, and explicitly multilevel memory) that are not encountered in serial or other parallel programming paradigms. Visibility into these elements is critical for troubleshooting and tuning applications that make use of CUDA. This paper will highlight CUDA concepts implemented in CUDA 3.0 - 4.0, the impact of those concepts for troubleshooting CUDA, and how TotalView helps users deal with these new CUDA-specific constructs. CUDA is frequently used alongside MPI parallelism and host-side multicore and multithread parallelism. The TotalView parallel debugger provides developers with an integrated view of all three levels of parallelism within a single debugging session.

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Transitioning to multicore: Part II

Multicore systems are ubiquitous; it’s virtually impossible to buy even commodity computers without a dual, quad, or hex-core processor. It won’t be long before many-core processors start to be prevalent as well. Each core in a multicore processor is capable of executing a program, so a quad-core processor can run four separate programs at the same time. That’s great if you have many different programs you need to run at one time, but can become a problem when you need performance from a single program. Those four cores can also potentially run one program faster than a single core processor would, but only if the program is written correctly. If you run a sequential (or serial) program written for single core architectures on a multicore platform, it will generally only be able to leverage a single core. Serial programs don’t run any faster, and may even run slightly slower, on multicore processors.

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