Dongho Ha

Orcid: 0009-0005-4090-4025

According to our database1, Dongho Ha authored at least 14 papers between 2021 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Layerwise retraining and freezing for multi-angle QAOA.
Quantum Mach. Intell., June, 2026

MaxiMoff: Designing Matrix Multiplication Accelerator for Effective Multiply-Add Operations Offloading.
IEEE Trans. Emerg. Top. Comput., 2026

DeSpa: Heterogeneous multi-core accelerators for energy-efficient dense and sparse computation at the tile level in Deep Neural Networks.
J. Syst. Archit., 2026

Carbon-Aware Continuous Learning for Sustainable Real-Time Machine Learning Analytics.
Proceedings of the 21st European Conference on Computer Systems, 2026

2025
BitL: A Hybrid Bit-Serial and Parallel Deep Learning Accelerator for Critical Path Reduction.
Proceedings of the 58th IEEE/ACM International Symposium on Microarchitecture, 2025

Avant-Garde: Empowering GPUs with Scaled Numeric Formats.
Proceedings of the 52nd Annual International Symposium on Computer Architecture, 2025

Effective Interplay between Sparsity and Quantization: From Theory to Practice.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024
M3XU: Achieving High-Precision and Complex Matrix Multiplication with Low-Precision MXUs.
Proceedings of the International Conference for High Performance Computing, 2024

Generalizing Ray Tracing Accelerators for Tree Traversals on GPUs.
Proceedings of the 57th IEEE/ACM International Symposium on Microarchitecture, 2024

Recompiling QAOA Circuits on Various Rotational Directions.
Proceedings of the 2024 International Conference on Parallel Architectures and Compilation Techniques, 2024

2023
MAD MAcce: Supporting Multiply-Add Operations for Democratizing Matrix-Multiplication Accelerators.
Proceedings of the 56th Annual IEEE/ACM International Symposium on Microarchitecture, 2023

TensorCV: Accelerating Inference-Adjacent Computation Using Tensor Processors.
Proceedings of the IEEE/ACM International Symposium on Low Power Electronics and Design, 2023

R2D2: Removing ReDunDancy Utilizing Linearity of Address Generation in GPUs.
Proceedings of the 50th Annual International Symposium on Computer Architecture, 2023

2021
Chapter Six - Deep learning with GPUs.
Adv. Comput., 2021


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