C++

I didnt know how to do that in C++ !

I've been reading through the C++ Cookbook (an oldie but a goodie – I assume that 99% of C++ out there is not modern C++, and modern C++ does not mean you don’t need to be able to grok templates, pointers etc – you may need to port something, or use a 3rd party lib) Anyway, reading through stream manipulators, from my understanding this is how you pass a generic 'delegate' into a constructor & invoke it: template<typename T, typename C> class ManipInfra { public: ManipInfra (basic_ostream<C>& ......

Posted On Thursday, January 10, 2013 6:31 AM | Comments (3)

Low-Latency High-Performant Financial App Infrastructures

Financial Apps feel the need for speed – this can come via parallelization, and via infrastructure - fast messaging and non-blocking distributed memory management. This blogpost gives an overview + examples of various technologies that can squeeze performance out of your trading apps and clock cycles out of your modeling apps. Low Latency via Infrastructure ZeroMQ · ZeroMQ is a messaging library - ‘messaging middleware’ , ‘TCP on steroids’ , ‘new layer on the networking stack’. not a complete messaging ......

Posted On Monday, March 26, 2012 9:05 PM | Comments (2)

Direct3D 11 Programming in a Nutshell

Programming Direct3D requires understanding of where different types of resources are bound to the shader pipeline. The shader pipeline consists of configurable fixed function stages (Input Shader, Tessellator, Stream Output, Rasterizer, Output merger), and opt-in HLSL programmable shader stages (Vertex Shader, Hull Shader, Domain Shader, Geometry Shader, Pixel Shader, Compute Shader). Passing data into shaders involves creating & binding resources to the pipeline in C++ on CPU, so that HLSL ......

Posted On Wednesday, March 14, 2012 10:28 AM | Comments (1)

C++ AMP

Overview C++ AMP is a GPGPU API – it allows you to define functions (kernels) that take some input, perform an expensive calculation on the GPU and return the output to CPU. GPU supports fast calculative operations across many SIMD-like cores - NVidia Tesla supports 512 cores compared to the paltry 10 cores available on the CPU today - even Intel's Knights Corner will only support 60 cores next year. Suitable only for certain classes of problems (i.e. data parallel algorithms) and not for others ......

Posted On Sunday, December 4, 2011 8:20 AM | Comments (1)

Post-Build C++ Skill Rebuild

· For the last decade, the majority of my dev work has leveraged the .NET Framework for construction of information systems. However, my interest has lain in numerical computing. · Is it possible to have an increasingly higher level of abstraction and at the same time achieve underlying high performance computing? The prevailing winds say no: C# is aimed at productivity, and C++ is for performance. Garbage collection was great, but do we still need it with the availability of smart pointers? Would ......

Posted On Saturday, October 29, 2011 9:59 PM | Comments (0)

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