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How to debug machine learning call stacks

Python is a popular language for deep learning but debugging calls to existing C/C++ code in shared libraries can be extremely challenging. Untangling the confusing maze of library calls, data translations, and linked-in CUDA code can be convoluted and time consuming, as neither Python nor C/C++ debuggers provide a comprehensive view across the languages.

In this video, recorded at GPU Technology Conference 2017, we look at how Python-C/C++ transformations combined with a multithreaded, multiprocess debugger helps you understand what’s going on within your deep learning code.

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TotalView for HPC

Faster fault isolation, improved memory optimization, and dynamic visualization for your high performance computing apps. TotalView for HPC is a scalable and intuitive debugger for parallel applications written in C, C++, and Fortran that simplifies and shortens the process of developing, debugging, and optimizing complex applications. Purpose-built for multicore and parallel computing, TotalView for HPC delivers a set of tools providing unprecedented control over processes and thread execution, along with deep visibility into program states and data.

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Memory error analysis in distributed applications

Memory bugs can have a disastrous effect on an applications usability. They are hard to track down because a variety of different situations cause them including overwriting the stack, not freeing the heap, or freeing it at the wrong time. It's difficult to trace back to a specific line of code because it can take a long time to manifest. And having to boot everyone off servers periodically and restart doesn't suffice when people rely on these servers. Read this paper to understand the root cause and how to resolve memory bugs.

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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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