410 Open source projects that are alternatives of or similar to hiperc

CUDAfy .NET allows easy development of high performance GPGPU applications completely from the .NET. It's developed in C#.

stdgpu: Efficient STL-like Data Structures on the GPU

Implementation of SYCL for CPUs, AMD GPUs, NVIDIA GPUs

The write-once-run-anywhere GPGPU library for Rust

GPGPU Javascript library 🐸

Thin C++-flavored wrappers for the CUDA Runtime API

The CHiMaD Phase Field Community Website

Algorithms implemented in CUDA + resources about GPGPU

Examples and demos for ReproZip

An efficient C++17 GPU numerical computing library with Python-like syntax

R interface to use GPU's

VexCL is a C++ vector expression template library for OpenCL/CUDA/OpenMP

Vulkan compute for people

Advanced Simulation Library - hardware accelerated multiphysics simulation platform.

Multi-device OpenCL kernel load balancer and pipeliner API for C#. Uses shared-distributed memory model to keep GPUs updated fast while using same kernel on all devices(for simplicity).

A Finite Difference Method Engine in C++

Python wrapper for MFEM

Phase field model for precipitate aging in ternary analogues to Ni-based superalloys

General purpose GPU compute framework for cross vendor graphics cards (AMD, Qualcomm, NVIDIA & friends). Blazing fast, mobile-enabled, asynchronous and optimized for advanced GPU data processing usecases.

GARDENIA: Graph Analytics Repository for Designing Efficient Next-generation Accelerators

software.intel.com/content/www/us/en/develop/articles/repo-evaluating-performance-productivity-oneapi.html

General purpose GPU compute framework built on Vulkan to support 1000s of cross vendor graphics cards (AMD, Qualcomm, NVIDIA & friends). Blazing fast, mobile-enabled, asynchronous and optimized for advanced GPU data processing usecases. Backed by the Linux Foundation.

CUDA integration for Python, plus shiny features

C++ library for solving large sparse linear systems with algebraic multigrid method

OpenCL for Rust

Fast Clojure Matrix Library

ArrayFire: a general purpose GPU library.

A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU and embedded devices via OpenMP, Cuda and OpenCL backends

GPU Mersenne primality test.

turbo.js - perform massive parallel computations in your browser with GPGPU.

Fitting thermodynamic models with pycalphad - https://doi.org/10.1557/mrc.2019.59

JIT Compilation for Multiple Architectures: C++, OpenMP, CUDA, HIP, OpenCL, Metal

Robotics with GPU computing

Converting vertex meshes to voxel data and visualizing using VCT

Educational Python implementation of the Canny Edge Detector

🏔 Procedural terrain using Three.js and perlin noise, Now Accelerated by your GPU!

Applied Matematical Methods in Materials Engineering

Intercept Layer for Debugging and Analyzing OpenCL Applications

Print all known information about all available OpenCL platforms and devices in the system

An Ontology for the Materials Design Domain

Spark extension for processing large-scale 3D data sets: Astrophysics, High Energy Physics, Meteorology, …

GPU Accelerated JavaScript

Vulkan 1.0 graphics and compute API bindings for .NET Standard

A docker-based starter kit for machine learning via jupyter notebooks. Designed for those who just want a runtime environment and get on with machine learning. Docker tags:

A real time optical flow algorithm implemented on GPU

GPU Framework for Radio Astronomical Image Synthesis

🧮 An Open Source, Parallel and Heterogeneous Finite Element Analysis Framework

STREAM, for lots of devices written in many programming models

Stream Processing with OCaml

A framework for the automated derivation and parallel execution of finite difference solvers on a range of computer architectures.

💥💻💥 A data-parallel functional programming language

World's fastest and most advanced password recovery utility

Benzina is an image-loader package that greatly accelerates image loading onto GPUs using their built-in hardware codecs.

Codes for text-mined solid-state reactions dataset

Examples and demos showing how to call functions from the NAG Library for Python

library of numerical methods using Armadillo

List of Machine Learning, AI, NLP solutions for iOS. The most recent version of this article can be found on my blog.

kramersmoyal: Kramers-Moyal coefficients for stochastic data of any dimension, to any desired order

Amplifier allows .NET developers to easily run complex applications with intensive mathematical computation on Intel CPU/GPU, NVIDIA, AMD without writing any additional C kernel code. Write your function in .NET and Amplifier will take care of running it on your favorite hardware.

An optimized OpenCL implementation of the Non-local means de-noising algorithm