__host__ __device__ -- Generic programming in Cuda

We present patterns for Cuda/C++ to write save generic code which works both on the host and device side. Writing templated functions in Cuda/C++ both for the CPU and the GPU bears the problem that in general both __host__ and __device__ functions are instantiated, which leads to lots of compiler warnings or errors.Comment: First draf

Lexiconic: Reading the Edifice

Language has undergone an evolution similar to architecture. Both have been defined through multiple styles which have a tendency to change and reestablish themselves based on popular culture, eventually permeating through society, while subsequently losing momentum and necessity. In the same way that architecture has transitioned through time based on a societal importance of efficiency, economy, and effectiveness, language begins to assume a new oratory standard. Old English begat Middle English begat Modern English Victorian Style begat Modernism begat Structural Expressionism These entities have become representative of our culture throughout the ages and have reached a point of abbreviation so severe that LOL has become accepted in our contemporary language in the same way that the recycled geometries of a builder’s suburbia are accepted in the built urban fabric. Common architecture that inhabits neighborhood streets and replicates empty strip malls is a simple form being pushed through an algorithmic system, with the core necessity of the building being ignored in favor of a quicker output. The same is happening to language: shortened words and poor grammar causes the orator to produce an idea quickly, but the audience to break down a sentence in order to understand the idea, adding an unnecessary setback to the mode of communication. Should we allow ourselves to be accommodating to a lack of effort by both common architecture and language, merely writing them off as an unfortunate fad? Or does this signify the transition to the next phase of evolution - in which case the issue is not whether this will continue, but where it will take us

Stability under dwell time constraints: Discretization revisited

We decide the stability and compute the Lyapunov exponent of continuous-time linear switching systems with a guaranteed dwell time. The main result asserts that the discretization method with step size~$h$ approximates the Lyapunov exponent with the precision~$C\,h^2$, where~$C$ is a constant. Let us stress that without the dwell time assumption, the approximation rate is known to be linear in~$h$. Moreover, for every system, the constant~$C$ can be explicitly evaluated. In turn, the discretized system can be treated by computing the Markovian joint spectral radius of a certain system on a graph. This gives the value of the Lyapunov exponent with a high accuracy. The method is efficient for dimensions up to, approximately, ten; for positive systems, the dimensions can be much higher, up to several hundreds