3 papers
cs.DB2025
Floating-Point Data Transformation for Lossless Compression
Samirasadat Jamalidinan, Kazem Cheshmi
Floating-point data is widely used across various domains. Depending on the required precision, each floating-point value can occupy several bytes. Lossless storage of this informa…
cs.PL2025
A Novel Compiler Transformation for Fast Sparse Matrix Multiplication in GPUs
Hossein Albakri, Kazem Cheshmi
Sparse data structures are commonly used in neural networks to reduce the memory footprint. These data structures are compact but cause irregularities such as random memory accesse…
cs.DC2024
Improving Locality in Sparse and Dense Matrix Multiplications
Mohammad Mahdi Salehi Dezfuli, Kazem Cheshmi
Consecutive matrix multiplications are commonly used in graph neural networks and sparse linear solvers. These operations frequently access the same matrices for both reading and w…