I would like to announce the release of termoshtt/accel, a CUDA-based GPGPU framework for Rust.This is an experimental project with three following key features. Although it has still several limitations, you can start hacking GPGPU computing in Rust 
I hope your feedback!
Compile PTX Kernel from Rust using NVPTX backend of LLVM
From 2017/2, we can compile Rust into a PTX assembla using NVPTX backend of LLVM as demonstrated in japaric/nvptx, however, it needs a complicated setting. Accel generates this setting automatically using procedural macro feature.
proc-macro-attribute-based approach like futures-await
accel-derive crate introduces a proc-macro #[kernel], which generates two functions. One is compiled into a PTX code, called "kernel", and the other calls it from CPU code using cudaLaunchKernel, called "caller". A support crate rust2ptx is created while the proc-macro at $HOME/.rust2ptx directory, and compiles the generated function (saved as lib.rs) using xargo. Generated PTX assembla is inserted into the source code of "caller" and thus embedded into the executable binary.
Simple memory management using Unified Memory
Unified memory (UM) is a feature introduced in CUDA6 and extended in CUDA8. We can manage memory without considering the memory is on CPU or GPU. Accel introduces accel::UVec struct which manage UM as RAII and you can use it as a slice through Deref.