2 repositorios
Java bindings that enable offloading parallel computation to GPUs via OpenCL or Vulkan compute.
Distinct from GPU Computations: Distinct from GPU Computations: provides managed-language bindings for GPU compute, not raw GPU programming.
Explore 2 awesome GitHub repositories matching hardware & iot · Managed GPU Compute Bindings. Refine with filters or upvote what's useful.
Gorgonia is a Go library that provides an automatic differentiation engine and a computation graph framework for building and training neural networks. It functions as a CUDA-accelerated tensor library and a SIMD-optimized math library, enabling machine learning workflows entirely within the Go ecosystem. The library distinguishes itself through a dual-backend architecture that dispatches neural network operations to either a GPU or CPU depending on CUDA availability at runtime. It constructs differentiable directed acyclic graphs of tensor operations, supports reverse-mode automatic gradient
Creates hardware-specific CUDA bindings using a code generation tool to enable GPU-accelerated computation.
LWJGL is a cross-platform library that provides Java bindings to native APIs for graphics, audio, compute, windowing, and input. It enables Java applications to access low-level hardware-accelerated capabilities such as OpenGL and Vulkan rendering, OpenAL 3D audio, OpenCL GPU compute, and GLFW windowing and input handling. Under the hood, LWJGL dynamically resolves native function pointers at runtime, loads platform-specific shared libraries, and uses generated JNI bindings to bridge Java and native code. It offers explicit memory management through direct buffer access and stack-allocated me
Offloads parallel computation tasks to GPUs via OpenCL or Vulkan compute from a Java runtime.