2 citations · 3 across the 17 of their papers we have counts for
9 papers · 1 filter
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…
Cyclotron: Compilation of Recurrences to Distributed and Systolic Architectures
Shiv Sundram, Akhilesh Balasingam, Nathan Zhang +2
We present Cyclotron, a framework and compiler for using recurrence equations to express streaming dataflow algorithms, which then get portably compiled to distributed topologies o…
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…
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…
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…
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…
Fast Collection Operations from Indexed Stream Fusion
Scott Kovach, Praneeth Kolichala, Kyle A. Miller +2
We present a system of efficient methods for traversing and combining associative collection data structures. A distinguishing feature of the system is that, like traditional seque…
Ember: A Compiler for Efficient Embedding Operations on Decoupled Access-Execute Architectures
Marco Siracusa, Olivia Hsu, Victor Soria-Pardos +8
Irregular embedding lookups are a critical bottleneck in recommender models, sparse large language models, and graph learning models. In this paper, we first demonstrate that, by o…
A Compiler for Operations on Relations with Bag Semantics
James Dong, Fredrik Kjolstad
We describe an abstract loop-based intermediate representation that can express fused implementations of relational algebra expressions on sets and bags (multisets). The loops are…