15 papers
Compiling Bioinformatics Recurrences
Bala Vinaithirthan, Shiv Sundram, Sneha Goenka +1
Many bioinformatics algorithms, such as sequence alignment and structure prediction, can be expressed as recurrence equations over a dynamic programming matrix. Efficient implement…
TensorBench: Benchmarking Coding Agents on a Compiler-Based Tensor Framework
Bobby Yan, Fredrik Kjolstad
Repository-level coding benchmarks face a trade-off between task difficulty and evaluation reliability: tasks that challenge frontier models often involve large codebases with inco…
Bonsai: Compiling Queries to Pruned Tree Traversals
Alexander J Root, Christophe Gyurgyik, Purvi Goel +4
Trees can accelerate queries that search or aggregate values over large collections. They achieve this by storing metadata that enables quick pruning (or inclusion) of subtrees whe…
Partitioning Unstructured Sparse Tensor Algebra for Load-Balanced Parallel Execution
Atharva Chougule, Alexander J Root, Rubens Lacouture +3
Sparse tensor algebra is challenging to efficiently parallelize due to the irregular, data-dependent, and potentially skewed structure of sparse computation. We propose the first p…
Decoupling Data Layouts from Bounding Volume Hierarchies
Christophe Gyurgyik, Alexander J Root, Fredrik Kjolstad
Bounding volume hierarchies are ubiquitous acceleration structures in graphics, scientific computing, and data analytics. Their performance depends critically on data layout choice…
FuseFlow: A Fusion-Centric Compilation Framework for Sparse Deep Learning on Streaming Dataflow
Rubens Lacouture, Nathan Zhang, Ritvik Sharma +4
As deep learning models scale, sparse computation and specialized dataflow hardware have emerged as powerful solutions to address efficiency. We propose FuseFlow, a compiler that c…