26 citations · 43 across the 12 of their papers we have counts for
14 papers
A Dynamic Intermediate Representation for Hybrid Quantum-Classical Programs
Alex Rice, Chris Heunen, Tobias Grosser
Quantum compilers typically follow the circuit model, representing programs as fixed sequences of gates. This static view breaks down in hybrid quantum-classical applications, wher…
Strided Difference Bound Matrices
Arjun Pitchanathan, Albert Cohen, Oleksandr Zinenko +1
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 their…
TensorFlow as a DSL for stencil-based computation on the Cerebras Wafer Scale Engine
Nick Brown, Brandon Echols, Justs Zarins +1
The Cerebras Wafer Scale Engine (WSE) is an accelerator that combines hundreds of thousands of AI-cores onto a single chip. Whilst this technology has been designed for machine lea…
MOM: Matrix Operations in MLIR
Lorenzo Chelini, Henrik Barthels, Paolo Bientinesi +3
Modern research in code generators for dense linear algebra computations has shown the ability to produce optimized code with a performance which compares and often exceeds the one…
Lambda the Ultimate SSA: Optimizing Functional Programs in SSA
Siddharth Bhat, Tobias Grosser
Static Single Assignment (SSA) is the workhorse of modern optimizing compilers for imperative programming languages. However, functional languages have been slow to adopt SSA and p…
QSSA: An SSA-based IR for Quantum Computing
Anurudh Peduri, Siddharth Bhat
Quantum computing hardware has progressed rapidly. Simultaneously, there has been a proliferation of programming languages and program optimization tools for quantum computing. Exi…