29 citations · 31 across the 10 of their papers we have counts for
10 papers
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…
Optimal Software Pipelining and Warp Specialization for Tensor Core GPUs
Rupanshu Soi, Rohan Yadav, Fredrik Kjolstad +4
GPU architectures have continued to grow in complexity, with recent incarnations introducing increasingly powerful fixed-function units for matrix multiplication and data movement…
On the Duality of Task and Actor Programming Models
Rohan Yadav, Joseph Guman, Sean Treichler +4
Programming models for distributed and heterogeneous machines are rapidly growing in popularity to meet the demands of modern workloads. Task and actor models are common choices th…
Mapple: A Domain-Specific Language for Mapping Distributed Programs
Anjiang Wei, Rohan Yadav, Hang Song +3
Optimizing parallel programs for distributed systems is a complex task, often requiring significant code modifications. Task-based programming systems improve modularity by separat…
Task-Based Tensor Computations on Modern GPUs
Rohan Yadav, Michael Garland, Alex Aiken +1
Domain-specific, fixed-function units are becoming increasingly common in modern processors. As the computational demands of applications evolve, the capabilities and programming i…
Improving Parallel Program Performance with LLM Optimizers via Agent-System Interfaces
Anjiang Wei, Allen Nie, Thiago S. F. X. Teixeira +4
Modern scientific discovery increasingly relies on high-performance computing for complex modeling and simulation. A key challenge in improving parallel program performance is effi…
Automatic Tracing in Task-Based Runtime Systems
Rohan Yadav, Michael Bauer, David Broman +3
Implicitly parallel task-based runtime systems often perform dynamic analysis to discover dependencies in and extract parallelism from sequential programs. Dependence analysis beco…
Composing Distributed Computations Through Task and Kernel Fusion
Rohan Yadav, Shiv Sundram, Wonchan Lee +4
We introduce Diffuse, a system that dynamically performs task and kernel fusion in distributed, task-based runtime systems. The key component of Diffuse is an intermediate represen…
SpDISTAL: Compiling Distributed Sparse Tensor Computations
Rohan Yadav, Alex Aiken, Fredrik Kjolstad
We introduce SpDISTAL, a compiler for sparse tensor algebra that targets distributed systems. SpDISTAL combines separate descriptions of tensor algebra expressions, sparse data str…
DISTAL: The Distributed Tensor Algebra Compiler
Rohan Yadav, Alex Aiken, Fredrik Kjolstad
We introduce DISTAL, a compiler for dense tensor algebra that targets modern distributed and heterogeneous systems. DISTAL lets users independently describe how tensors and computa…