116 citations · 136 across the 9 of their papers we have counts for
10 papers
Flashlight: PyTorch Compiler Extensions to Accelerate Attention Variants
Bozhi You, Irene Wang, Zelal Su Mustafaoglu +5
Attention is a fundamental building block of large language models (LLMs), so there have been many efforts to implement it efficiently. For example, FlashAttention leverages tiling…
MSCCL++: Rethinking GPU Communication Abstractions for AI Inference
Changho Hwang, Peng Cheng, Roshan Dathathri +12
AI applications increasingly run on fast-evolving, heterogeneous hardware to maximize performance, but general-purpose libraries lag in supporting these features. Performance-minde…
Optimizing Graph Transformer Networks with Graph-based Techniques
Loc Hoang, Udit Agarwal, Gurbinder Gill +4
Graph transformer networks (GTN) are a variant of graph convolutional networks (GCN) that are targeted to heterogeneous graphs in which nodes and edges have associated type informa…
Sandslash: A Two-Level Framework for Efficient Graph Pattern Mining
Xuhao Chen, Roshan Dathathri, Gurbinder Gill +2
Graph pattern mining (GPM) is used in diverse application areas including social network analysis, bioinformatics, and chemical engineering. Existing GPM frameworks either provide…
EVA: An Encrypted Vector Arithmetic Language and Compiler for Efficient Homomorphic Computation
Roshan Dathathri, Blagovesta Kostova, Olli Saarikivi +3
Fully-Homomorphic Encryption (FHE) offers powerful capabilities by enabling secure offloading of both storage and computation, and recent innovations in schemes and implementations…
An Adaptive Load Balancer For Graph Analytical Applications on GPUs
Vishwesh Jatala, Loc Hoang, Roshan Dathathri +3
Load-balancing among the threads of a GPU for graph analytics workloads is difficult because of the irregular nature of graph applications and the high variability in vertex degree…
Pangolin: An Efficient and Flexible Graph Pattern Mining System on CPU and GPU
Xuhao Chen, Roshan Dathathri, Gurbinder Gill +1
There is growing interest in graph pattern mining (GPM) problems such as motif counting. GPM systems have been developed to provide unified interfaces for programming algorithms fo…
Distributed Training of Embeddings using Graph Analytics
Gurbinder Gill, Roshan Dathathri, Saeed Maleki +3
Many applications today, such as NLP, network analysis, and code analysis, rely on semantically embedding objects into low-dimensional fixed-length vectors. Such embeddings natural…
Single Machine Graph Analytics on Massive Datasets Using Intel Optane DC Persistent Memory
Gurbinder Gill, Roshan Dathathri, Loc Hoang +2
Intel Optane DC Persistent Memory (Optane PMM) is a new kind of byte-addressable memory with higher density and lower cost than DRAM. This enables the design of affordable systems…
CHET: Compiler and Runtime for Homomorphic Evaluation of Tensor Programs
Roshan Dathathri, Olli Saarikivi, Hao Chen +5
Fully Homomorphic Encryption (FHE) refers to a set of encryption schemes that allow computations to be applied directly on encrypted data without requiring a secret key. This enabl…