GitHub topics: accelerated-computing
NVIDIA/cccl
CUDA Core Compute Libraries
Language: C++ - Size: 81.6 MB - Last synced at: 6 days ago - Pushed at: 6 days ago - Stars: 1,667 - Forks: 220
HROlive/Fundamentals-of-Accelerated-Data-Science
How to use GPU-accelerated tools to conduct data science faster, leading to more scalable, reliable, and cost-effective results.
Language: Jupyter Notebook - Size: 33.1 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0
z1skgr/SIMD-instruction-MPI-PTHREADS-parallism
Parallelism standards for accelerating performance on calculations for detection of positive DNA selection
Language: C - Size: 866 KB - Last synced at: 2 months ago - Pushed at: 7 months ago - Stars: 2 - Forks: 0
HROlive/Fundamentals-of-Accelerated-Computing-with-CUDA-Python
Explore how to use Numba—the just-in-time, type-specializing Python function compiler—to create and launch CUDA kernels to accelerate Python programs on massively parallel NVIDIA GPUs.
Size: 4.41 MB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 0 - Forks: 0
HengruiZYP/Yolov3-NPU-Acceleration
Accelerating YOLOv3 model inference using NPU.
Language: Python - Size: 152 MB - Last synced at: 9 months ago - Pushed at: 9 months ago - Stars: 1 - Forks: 0
HengruiZYP/Hrnet-NPU-Acceleration
Accelerating Hrnet model inference using Neural Processing Unit (NPU).
Language: Python - Size: 81.5 MB - Last synced at: 9 months ago - Pushed at: 9 months ago - Stars: 1 - Forks: 0
HengruiZYP/Resent-NPU-Acceleration
Accelerating Resnet model inference using NPU.
Language: Python - Size: 27.8 MB - Last synced at: 9 months ago - Pushed at: 9 months ago - Stars: 1 - Forks: 0
abhilash1910/My-Talks-and-Sessions
Talks and Presentations on Deep Learning principles,models and architectures
Size: 6.84 KB - Last synced at: 3 days ago - Pushed at: 12 months ago - Stars: 0 - Forks: 0
cepdnaclk/e16-4yp-Acceleration-of-DTW-algorithm-for-real-time-nanopore-selective-sequencing-using-GPUs
The project aims to optimize the Dynamic Time Warping (DTW) algorithm and accelerate it using Graphics Processing Units (GPUs), So that algorithm can be executed in a GPU-equipped laptop or a GPU-equipped embedded device like NVIDIA Jetson, rather than connecting to a massive server.
Size: 64 MB - Last synced at: 3 months ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 1
Paperspace/CORE-API-Docs
Paperspace CORE API Documentation
Size: 257 KB - Last synced at: 2 months ago - Pushed at: almost 4 years ago - Stars: 1 - Forks: 0
itzmeanjan/ff-gpu 📦
Finite Field Operations on GPGPU
Language: C++ - Size: 265 KB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 10 - Forks: 1
axelvanherle/imgConvolutionCuda-C 📦
Written by Sem Kirkels, Nathan Bruggeman and Axel Vanherle. Grayscales an image, applies convolution, maximum pooling and minimum pooling.
Language: Jupyter Notebook - Size: 373 MB - Last synced at: almost 2 years ago - Pushed at: over 2 years ago - Stars: 2 - Forks: 0
SousaPedroso/CUDA
My solutions for NVIDIA course Fundamentals of Accelerated Computing with CUDA C/C++
Language: Cuda - Size: 21.5 KB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0
mjkim1001/asc19-project
Advance Statistical Computing, 2019, Seoul National University
Language: Jupyter Notebook - Size: 5.09 MB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0
shumbul/Accelerated-Computing
Fundamentals of Accelerated Computing C/C++ is a course provided by NVIDIA.
Language: Cuda - Size: 42 KB - Last synced at: over 2 years ago - Pushed at: over 4 years ago - Stars: 1 - Forks: 0
