• CUDA

  • Referenced in 1234 articles [sw03258]
  • environment for C and C++ developers building GPU-accelerated applications. The CUDA Toolkit includes...
  • PyTorch

  • Referenced in 245 articles [sw20939]
  • Dynamic neural networks in Python with strong GPU acceleration. PyTorch is a deep learning framework...
  • CUBLAS

  • Referenced in 80 articles [sw06880]
  • computational resources of NVIDIA Graphics Processing Unit (GPU), but does not auto-parallelize across multiple ... required matrices and vectors in the GPU memory space, fill them with data, call ... then upload the results from the GPU memory space back to the host. The CUBLAS ... writing and retrieving data from the GPU...
  • OpenGL

  • Referenced in 131 articles [sw06740]
  • interact with a Graphics processing unit (GPU), to achieve hardware-accelerated rendering. OpenGL was developed...
  • Keras

  • Referenced in 131 articles [sw15491]
  • output training). runs seamlessly on CPU and GPU. Read the documentation at Keras.io. Keras...
  • Nektar++

  • Referenced in 78 articles [sw11964]
  • elliptic finite element method to the GPU and perform a case study for a particular ... This study provides comparison between CPU and GPU implementations of the method as well ... method is well-suited for GPU implementation, obtaining total speedups on the order...
  • Theano

  • Referenced in 81 articles [sw05894]
  • integration with numpy, transparent use of a GPU, efficient symbolic differentiation, speed and stability optimizations...
  • MAGMA

  • Referenced in 54 articles [sw12741]
  • heterogeneous/hybrid architectures, starting with current ”Multicore+GPU” systems. The MAGMA research is based ... algorithms and frameworks for hybrid manycore and GPU systems that can enable applications to fully...
  • U-Net

  • Referenced in 71 articles [sw33176]
  • less than a second on a recent GPU. The full implementation (based on Caffe...
  • SPIRAL

  • Referenced in 46 articles [sw00903]
  • variety of platforms including SSE, multicore, Cell, GPU, distributed memory parallel processors, and FPGA...
  • Numba

  • Referenced in 43 articles [sw21554]
  • Python to run on either CPU or GPU hardware, and is designed to integrate with...
  • GTEngine

  • Referenced in 42 articles [sw24041]
  • supports high-performance computing using general purpose GPU programming (GPGPU). SIMD code is also available...
  • ASTRA

  • Referenced in 30 articles [sw14524]
  • MATLAB toolbox based on high-performance GPU primitives for 2D and 3D tomography, developed jointly ... basic forward and backward projection operations are GPU-accelerated, and directly callable from MATLAB...
  • StarPU

  • Referenced in 40 articles [sw14216]
  • opteron processors. Other architectures, featuring GPU accelerators, are expected to appear in the near future...
  • MUMMER

  • Referenced in 40 articles [sw17256]
  • Biology paper. We have also developed a GPU accelerated version of MUMmer called MUMmerGPU...
  • cuFFT

  • Referenced in 24 articles [sw11258]
  • interface for computing FFTs on an NVIDIA GPU, which allows users to quickly leverage ... floating-point power and parallelism of the GPU in a highly optimized and tested...
  • GPGPU

  • Referenced in 20 articles [sw09105]
  • computation on graphics hardware. The graphics processor (GPU) on today’s commodity video cards ... review the tools, perils, and strategies in GPU programming. We present analysis of GPU performance...
  • laGP

  • Referenced in 21 articles [sw14043]
  • vast out-of-sample testing set; GPU acceleration is also supported for an important subroutine ... OpenMP and GPU features may require special compilation. An interface to lower-level (full...
  • BADMM

  • Referenced in 27 articles [sw20288]
  • massive parallelism and can easily run on GPU. BADMM is several times faster than highly...