Author

Jia-Jia Li

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Preprint Sep 2026

DejaVu: Unifying Memory Allocations to Eliminate Redundant Copies on Unified-Memory SoCs

GPU applications on unified-memory (UMA) edge platforms often inherit a discrete-GPU memory abstraction in which they allocate one buffer for the CPU, another for the GPU, and copy data between them before and after GPU execution. On UMA hardware these buffers reside in the same physical DRAM, so the copies consume ban...

Yu-Heng Zhu, Yan-Bo Zhao, Jia-Jia Li et al. · 0 citations

Preprint Sep 2026

Scaling Fourier-Based Sparse Matrix Analysis on GPUs

Sparse computations are important workloads in applications such as scientific computing, graph neural networks (GNNs), and machine learning. While many sparse operations can benefit from modern GPUs, the sparsity pattern remains important to performance because it affects memory coalescing, block organization, and loa...

Rui-Feng Zhang, Sai Akhil Varma Manthena, Jia-Jia Li et al. · 0 citations