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"How to test static_assert" and "The Blaze High Performance Math Library"

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"How to test static_assert" and "The Blaze High Performance Math Library"

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Title: How to test static_assert

Presenter: Roland Bock

Language: English

Abstract: static_assert gives us the ability to assert conditions at compile time and provide custom error messages in case the conditions are not met. Cool! But how can you be sure that your precious static_asserts actually fire when you need them? There is only one way to know for sure:

You need to test your static_assert!

That is easier said than done, though, as static_assert produces a hard, unrecoverable compile-time error. For instance, you cannot test one static_assert with another.

This talk will demonstrate several options for testing static_assert, ranging from the build system, over the compiler features to template meta programming. It will include real-life examples from sqlpp11.

Link: https://cppcon2016.sched.org/event/7nKk/how-to-test-staticassert

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Title: The Blaze High Performance Math Library

Presenter: Klaus Iglberger

Language: English

Abstract: Scientific computing requires a developer to tackle enormous complexities, both from a scientific and from a programming point of view. In order to be able to focus on the complexities arising from the application domain, the programming part should be simplified as much as possible. One way to achieve this, is to rely on the powers of an advanced math library, which takes care of difficult aspects like data layout, algorithms, vectorization, and parallelization.

One of these advanced math libraries is Blaze (https://bitbucket.org/blaze-lib/blaze). Blaze is an open-source, high-performance C++ math library for dense and sparse arithmetic. Blaze combines elegance and ease of use with HPC-grade performance, making it one of the most intuitive and at the same time fastest C++ math libraries available.

This presentation demonstrates why Blaze is a great addition to every toolchain. Additionally, it focuses on the customizability aspect that enables users to adapt Blaze to special circumstances: block structured vectors and matrices, custom data structures and operations, and a customizable error reporting mechanism.

Link: https://cppcon2016.sched.org/event/7nLF/the-blaze-high-performance-math-library

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