EM Photonics has released a beta version of CULA, an implementation of the LAPACK linear algebra library designed and optimised for NVIDIA’s massively parallel CUDA-enabled graphics processing units (GPUs).
The company claimed that the developers that rely on LAPACK routines for solving problems ranging from computational physics and structural mechanics to electronic design automation can now get up to a 10X boost in performance over a single quad-core CPU(1) by using NVIDIA Tesla GPUs in their workstation or datacentre.
The company has partnered with NVIDIA to release the new offering.
EM Photonics’ CULAtools is a product family comprising CULA Basic, Premium, and Commercial. The CULA library is reportedly a GPU-accelerated implementation of the LAPACK routines. LAPACK is a collection of commonly used functions in linear algebra, used by developers in the scientific and engineering community.
The company said that the problems they tackle can be approximated by linear models and can be solved using linear algebra routines. CULA uses the massively parallel CUDA architecture of NVIDIA’s GPUs to enhance many of the common LAPACK routines.
Andy Keane, general manager of the Tesla business unit at NVIDIA, said: Our customer base has been anticipating the release of a linear algebra library similar to LAPACK. This fundamental math library brings the power of GPU computing to a much broader developer base in the scientific computing community.
“CULA forms yet another key branch in our rapidly increasing ecosystem of CUDA libraries which now includes FFT, BLAS, image processing, computer vision, ray tracing, rendering, molecular dynamics, and more.
