KokkosKernels implements local computational kernels for linear algebra and graph operations, using the Kokkos shared-memory parallel programming model. "Local" means not using MPI, or running within ...
Matrix structures don’t work on their own. The work is less about control and more about integration, often without formal ...
Learning to program in C on an online platform can provide structured learning and a certification to show along with your resume. Learning C can still be useful in 2026, especially if you want to ...
Abstract: This article presents a high-precision close-to-analog programming methodology for phase-change memory (PCM) cells, targeting analog in-memory computing (AiMC) architectures for ...
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Its automatic differentiation capability enables algorithms written in C++ to be differentiated with little code modification, very useful for a wide range of applications that involve mathematical ...
Particles with internal inclusions or cores are ubiquitous in the atmosphere. One example is dust particles coated with water-soluble aerosols such as sulfate or nitrate. For these particles, the dust ...
Abstract: General Matrix Multiplication or GEMM kernels take centre place in high performance computing and machine learning. Recent NVIDIA GPUs include GEMM accelerators, such as NVIDIA’s Tensor ...
Inverting a matrix is one of the most common tasks in data science and machine learning. In this article I explain why inverting a matrix is very difficult and present code that you can use as-is, or ...
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