Philip Lassen

Representation and Reference Lowering of ONNX Models in MLIR Compiler Infrastructure

Multi-backend GPU query engine written with Futhark

:boom::computer::boom: A data-parallel functional programming language

My attempt at a thesis

Awk on the GPU

A place to play around with ONNX and its internal representation

A library for scraping sports data

a Haskell implementation of sqlite

No description.

A GPU database for Analytical SQL queries

Some scripts for butchering ONNX graphs

Open standard for machine learning interoperability

Classwork for Parallel Functional Programming (PFP)

No description.

No description.

Notes, experiments, and code stubs for my thesis

Tool for automatically adding and removing print statements for the lazy

No description.

The LLVM Project is a collection of modular and reusable compiler and toolchain technologies. Note: the repository does not accept github pull requests at this moment. Please submit your patches at http://reviews.llvm.org.

The Torch-MLIR project aims to provide first class support from the PyTorch ecosystem to the MLIR ecosystem.

Tensors and Dynamic neural networks in Python with strong GPU acceleration

wc utility written with and fo

Backward compatible ML compute opset inspired by HLO/MHLO

No description.

ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator

Cuda implementation of the wc utility

A simple Futhark Kernel for IPython

A tool for remembering facts and definitions

Open deep learning compiler stack for cpu, gpu and specialized accelerators

An implementation of awk

Textbook Solutions to Computer Systems

Seam rewrite

Make Futhark libraries in C++

Emscripten: An LLVM-to-WebAssembly Compiler

Futhark in the Browser...

Parallel Programming in Futhark

8-ary heap