16 citations · 33 across the 7 of their papers we have counts for
11 papers
SigmaTrace: Library-Agnostic Observability for CPU/GPU-Initiated RDMA Communication
Javid Baydamirli, Didem Unat
RDMA networking enables low-latency, high-bandwidth communication on large systems. Despite its adoption, however, observability is lacking. Existing tools target specific communic…
Multi-GPU Communication Schemes for Iterative Solvers: When CPUs are Not in Charge
Ismayil Ismayilov, Javid Baydamirli, Doğan Sağbili +2
This paper proposes a fully autonomous execution model for multi-GPU applications that completely excludes the involvement of the CPU beyond the initial kernel launch. In a typical…
Static Bootstrap Placement for Encrypted Language Model Decoding
Halil Ibrahim Kanpak, Didem Unat
Language models increasingly serve prompts that carry private data, and secure inference under homomorphic encryption lets a client outsource the computation without revealing the…
GPU-Initiated Communication: Dissecting Down to the Bone
Javid Baydamirli, Ismayil Ismayilov, Kaan Oktay +1
GPU-initiated communication lets GPU threads post RDMA operations directly to the NIC. It underpins NVSHMEM, NCCL GIN, and DeepEP, which serve the fine-grained, latency-critical co…
ucTrace: A Multi-Layer Profiling Tool for UCX-driven Communication
Emir Gencer, Mohammad Kefah Taha Issa, Ilyas Turimbetov +2
UCX is a communication framework that enables low-latency, high-bandwidth communication in HPC systems. With its unified API, UCX facilitates efficient data transfers across multi-…
The Landscape of GPU-Centric Communication
Didem Unat, Ilyas Turimbetov, Mohammed Kefah Taha Issa +4
In recent years, GPUs have become the preferred accelerators for HPC and ML applications due to their parallelism and fast memory bandwidth. While GPUs boost computation, inter-GPU…
A Sparse Tensor Generator with Efficient Feature Extraction
Tugba Torun, Ameer Taweel, Didem Unat
Sparse tensor operations are increasingly important in diverse applications such as social networks, deep learning, diagnosis, crime, and review analysis. However, a major obstacle…
Monitoring Collective Communication Among GPUs
Muhammet Abdullah Soyturk, Palwisha Akhtar, Erhan Tezcan +1
Communication among devices in multi-GPU systems plays an important role in terms of performance and scalability. In order to optimize an application, programmers need to know the…
TIGER: Topology-aware Assignment using Ising machines Application to Classical Algorithm Tasks and Quantum Circuit Gates
Anastasiia Butko, Ilyas Turimbetov, George Michelogiannakis +3
Optimally mapping a parallel application to compute and communication resources is increasingly important as both system size and heterogeneity increase. A similar mapping problem…
A Computational-Graph Partitioning Method for Training Memory-Constrained DNNs
Fareed Qararyah, Mohamed Wahib, Doğa Dikbayır +2
Many state-of-the-art Deep Neural Networks (DNNs) have substantial memory requirements. Limited device memory becomes a bottleneck when training those models. We propose ParDNN, an…
BoxLib with Tiling: An AMR Software Framework
Weiqun Zhang, Ann Almgren, Marcus Day +3
In this paper we introduce a block-structured adaptive mesh refinement (AMR) software framework that incorporates tiling, a well-known loop transformation. Because the multiscale,…