The NVIDIA CUDA Basic Linear Algebra Subroutines (cuBLAS) library is a GPU-accelerated version of the complete standard BLAS library that delivers 6x to 17x faster performance than the latest MKL BLAS.
Building on the GPU-accelerated BLAS routines in the cuBLAS library, heterogeneous LAPACK implementations such as CULA Tools and MAGMA are also available.
This week’s Spotlight is on Valerie Halyo, assistant professor of physics at Princeton University.
Researchers in the field of high energy physics, such as Valerie, are exploring the most fundamental questions about the nature of the universe, looking for the elementary particles that constitute matter and its interactions.
One of Valerie’s goals is to extend the physics accessible at the Large Hadron Collider (LHC) at CERN in Geneva, Switzerland to include a larger phase space of the topologies that include long-lived particles. This research goes hand in hand with new ideas related to enhancing the “trigger” performance at the LHC.
(In particle physics, a trigger is a system that rapidly decides which events in a particle detector to keep when only a small fraction of the total can be recorded.)
Read Valerie’s full Spotlight here. Here is an excerpt:
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