GARIMELLA, Karthik, NEDA, Negar, EBEL, Austin, JHA, Nandan Kumar und REAGEN, Brandon, 2025. Network and Compiler Optimizations for Efficient Linear Algebra Kernels in Private Transformer Inference (Invited Paper). In: . 26 Oktober 2025.
Elsevier - Harvard (with titles)Garimella, K., Neda, N., Ebel, A., Jha, N.K., Reagen, B., 2025. Network and Compiler Optimizations for Efficient Linear Algebra Kernels in Private Transformer Inference (Invited Paper), in: . https://doi.org/10.1109/ICCAD66269.2025.11240733
American Psychological Association 7th editionGarimella, K., Neda, N., Ebel, A., Jha, N. K., & Reagen, B. (2025, Oktober 26). Network and Compiler Optimizations for Efficient Linear Algebra Kernels in Private Transformer Inference (Invited Paper). https://doi.org/10.1109/ICCAD66269.2025.11240733
Springer - Basic (author-date)Garimella K, Neda N, Ebel A, Jha NK, Reagen B (2025) Network and Compiler Optimizations for Efficient Linear Algebra Kernels in Private Transformer Inference (Invited Paper)
Juristische Zitierweise (Stüber) (Deutsch)Garimella, Karthik/ Neda, Negar/ Ebel, Austin/ Jha, Nandan Kumar/ Reagen, Brandon, Network and Compiler Optimizations for Efficient Linear Algebra Kernels in Private Transformer Inference (Invited Paper), 2025, .