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Numba: High-Performance Python with CUDA Acceleration
Numba is an open-source Python compiler from Anaconda that can compile Python code for high-performance execution on CUDA-capable GPUs or multicore CPUs.
NVIDIA Developer Blog
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CUDA on Windows Subsystem for Linux 2
In response to popular demand, Microsoft announced a new feature of the Windows Subsystem for Linux 2 (WSL 2)—GPU acceleration—at the Build conference in May 2020. This feature opens the gate for many…
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An Even Easier Introduction to CUDA
A quick and easy introduction to CUDA programming for GPUs. This post dives into CUDA C++ with a simple, step-by-step parallel programming example.
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How Jet Built a GPU-Powered Fulfillment Engine with F# and CUDA
Have you ever looked at your shopping list and tried to optimize your trip based on things like distance to store, price, and number of items you can buy at each store? The quest for a smarter…
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Hybridizer: High-Performance C# on GPUs
Hybridizer is a compiler from Altimesh that lets you program GPUs and other accelerators from C# code or .NET Assembly. Using decorated symbols to express parallelism, Hybridizer generates source code…
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Accelerated “Ray Tracing in One Weekend” in CUDA
Recent announcements of NVIDIA’s new Turing GPUs, RTX technology, and Microsoft’s DirectX Ray Tracing have spurred a renewed interest in ray tracing. Using these technologies vastly simplifies the…
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High-Performance GPU Computing in the Julia Programming Language
Julia is a high-level programming language for mathematical computing that is as easy to use as Python, but as fast as C. The language has been created with performance in mind…
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High-Performance GPU Computing in the Julia Programming Language (2017)
Julia is a high-level programming language for mathematical computing that is as easy to use as Python, but as fast as C. The language has been created with performance in mind…