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Open Source Strikes Again: Accelerated Math Libraries at AMD

Over the course of the past month or two, you may have seen a series of articles from our engineers on open source libraries. These libraries are aimed at accelerating math calculations for high...

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clFFT Pre-callback – A Faster Way to Pre-Process Data

clFFT Pre-callback – A Faster Way to Pre-Process Input Data The math library group at AMD is continuously looking for areas of improvement in the library and working towards optimizing the same. In his...

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AMD ACL 1.0 Beta 2: A Slew of Features & Improvements

In August of this year, AMD released the first version of the AMD Compute Library (ACL), a consolidated package providing the clBLAS, clFFT, clSPARSE, and clRNG libraries under one roof. Encouraged by...

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General Sparse Matrix–Sparse Matrix Multiplication (SpGEMM)

Beta 2 of the clSPARSE library introduces sparse matrix–sparse matrix multiplication (SpGEMM) function, which currently supports the single-precision CSR format for sparse storage. Weifeng Liu...

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AutoGemm: A flexible and high-performance solution to multiplying matrices

Our ACL 1.0 Beta 2 release contains several new features (that you can read more about here). One of those is AutoGemm, which is a new approach for achieving peak GEMM (GEneric Matrix Matrix...

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Improve FFT post-processing performance using clFFT Post-callback

In my previous blog, I explained the pre-callback feature of the clFFT library that gives a new and faster way to pre-process input data before the FFT operation is performed. Instead of the...

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Calculating large FFTs in memory-constrained systems

­ AMD Compute Library (ACL) 1.0 GA (General Availability) includes some new features and improvements over beta2 (for more information, click here). The ACL clFFT library includes the ability to...

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AMD ACL 1.0 GA Now Available

In October 2015, AMD released the AMD ACL 1.0 Beta 2, the second version of the AMD Compute Library (ACL), which provided important improvements in the clBLAS, clFFT, and clSPARSE libraries relative to...

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