Sabanci University CS406 Group Project Parallel Computing Cycle Count of length k in Sparse Matrix
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Updated
Jun 17, 2021 - Cuda
Sabanci University CS406 Group Project Parallel Computing Cycle Count of length k in Sparse Matrix
Repository for ICS'25: MG-𝛼GCD: Accelerating Graph Community Detection on Multi-GPU Platforms
A CUDA-based multi-GPU vertex-centric graph processing framework based on Warp Segmentation and Vertex Refinement techniques.
Measure bandwidth of multiple simultaneously started cudaMemcpyAsync
Source code for the CPU-Free model - a fully autonomous execution model for multi-GPU applications that completely excludes the involvement of the CPU beyond the initial kernel launch.
GPU Framework for Radio Astronomical Image Synthesis
Artifact for OSDI'23: MGG: Accelerating Graph Neural Networks with Fine-grained intra-kernel Communication-Computation Pipelining on Multi-GPU Platforms.
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