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Compute engine for executing kernels on multiple devices

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Popcorn

Popcorn is a library for executing parallel computation across different hardware devices. Just think of all the kernels you'll be cooking up.

Design Principles

Some basic design choices of Popcorn.

Buffers

A buffer is a piece of memory that can be stored in one or more devices. Depending on the different backend APIs used, buffers will be synchronized between different devices as needed. Buffers always have a "latest copy", which indicates the most up-to-date version of the buffer and which device it is on. This is used to determine if an actual sync is needed or not when executing an operation on the data.

Future-Based API

Never block if we can help it. OpenCL, CUDA and your CPU offer asynchronous memory synchronization between the various devices. This means we can abstract synchronization events as futures. This means a synchronization event between devices won't block the calling thread, so it can continue to queue other commands for different buffers.

Buffers are consumed into a future by every operation. This ensures that you can only ever access the most up-to-date version of the buffer via the future that is returned for every operation.

Generic

Popcorn is generic across a set of supported devices: OpenCL, CUDA, CPU, and Raspberry Pi GPU. We focus on generic use first and then on device-specific optimizations.

Thank You Collenchyma

The Collenchyma codebase provided a great starting point for Popcorn. The folks at Autumn.ai did a wonderful job pushing Rust forward in the machine learning community.

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