A key challenge for hardware acceleration of robotics applications is the enormous diversity
of possible deployment scenarios. To create efficient accelerators while minimizing non …

The end of Moore's Law and Dennard Scaling has combined with advances in agile
hardware design to foster a golden age of domain-specific acceleration. However, this new …

Designing compiler intermediate representations (IRs) is often a manual process that makes
exploration and innovation in this space costly. Developers typically use general-purpose …

We demonstrate a new approach to implementing automated coverage metrics including
line, toggle, and finite state machine coverage. Each metric is implemented through a …

Multi-Level Intermediate Representation (MLIR) is a novel compiler infrastructure that aims
to provide modular and extensible components to facilitate building domain specific …

Formats for representing and manipulating verification problems are extremely important for
supporting the ecosystem of tools, developers, and practitioners. A good format allows …

A wide range of symbolic analysis and optimization problems can be formalized using
polyhedra. Sub-classes of polyhedra, also known as sub-polyhedral domains, are sought for …

While traditional HLS (High-Level Synthesis) converts “high-level” C-like programs into
hardware automatically, producing high-performance designs still requires hardware …

Domain Specific Languages (DSLs) increase programmer productivity and provide high
performance. Their targeted abstractions allow scientists to express problems at a high level …

Tensor algebra is a crucial component for data-intensive workloads such as machine
learning and scientific computing. As the complexity of data grows, scientists often encounter …