Hardware Accelerator Generation

Filament, an HDL for Fearless Hardware Design

Filament is a new hardware design language that uses a substructural type system to reason about low-level programs and ensure that they generate correct and efficient hardware.

Calyx, an Infrastructure for Hardware Accelerator Compilers

We’re designing Calyx, an intermediate language (IL) and infrastructure for building compilers that generate hardware accelerators. Calyx works by representing both hardware-like structure and software-like control together. Calyx is a part of the LLVM CIRCT project and supports Cider and Pollen. You can try Calyx in your browser.

Dahlia, a Language for Predictable Accelerator Design

High-level synthesis (HLS) tools can translate C-like languages to hardware accelerators, but the semantic gap between software and hardware can yield unpredictable performance and semantics. Dahlia adds a substructural type system to model hardware resources and their constraints to statically reject HLS designs that make unpredictable area-latency trade-offs. You can try Dahlia in your browser.

Graphics Programming

Gator: Geometry Types

We have identified a new category of geometry bugs that arise in graphics programming and other domains that have to deal with matrices and vectors. They arise when programmers lose track of the coordinate systems and reference frames that underpin the computation. Gator is a language for GPU shading with a type system that can eliminate geometry bugs and rule them out by generating correct-by-construction transformation code.

Braid, a Safe Heterogeneous Language for Real-Time Graphics

Braid is a programming language for heterogeneous programming, where a single source program targets different hardware units. We have applied it to real-time graphics programming on CPU–GPU systems. Braid compiles to WebGL, so you can try it out in your browser.

Search-Based Compilation for Digital Signal Processing

Digital signal processors (DSPs) are ubiquitous and energy efficient, but making them fast requires an expert programmer. The difficulty stems from their complex vector instruction sets and simple, in-order pipelines. To get the best results, programmers must carefully pack and move data in vector registers to enable compact execution. Diospyros uses equality saturation to automatically discover efficient vector packing schemes.

Vision/System Co-Design

Customizing JPEG Compression for Computer Vision

Image compression formats like JPEG are ubiquitous in computer vision, but they were designed for human perception—not for modern vision algorithms. We examine the potential for customizing JPEG compression for specific vision tasks, simultaneously improving compression the ratio and the accuracy.

Exploiting Temporal Redundancy for Live Computer Vision

Vision accelerators that run on real-time video process nearly identical frames at every time step. This project introduces activation motion compensation, a technique for approximately incremental acceleration of computer vision. It works by measuring motion in the input video and translating it to motion in the intermediate results of convolutional neural networks.

A Vision Mode for Efficient Image Capture

Most camera systems are optimized for photography, so they waste time and energy when they capture images for computer vision. This project designs a vision mode for cameras and their associated signal processing logic that saves energy by producing lower-quality, less-processed image data.