Author:
Mpakos Panagiotis,Tasou Ioanna,Alverti Chloe,Miliadis Panagiotis,Malakonakis Pavlos,Theodoropoulos Dimitris,Goumas Georgios,Pnevmatikatos Dionisios N.,Koziris Nectarios
Publisher
Springer Nature Switzerland
Reference20 articles.
1. Attarde, S., Joshi, S., Deshpande, Y., Puranik, S., Patkar, S.: Double precision sparse matrix vector multiplication accelerator on FPGA. In: International Conference on Pervasive and Embedded Computing and Communication Systems, pp. 476–484. IEEE (2021)
2. Chen, X., Tan, H., Chen, Y., He, B., Wong, W.F., Chen, D.: ThunderGP: HLS-based graph processing framework on FPGAs. In: The 2021 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, pp. 69–80 (2021)
3. Du, Y., Hu, Y., Zhou, Z., Zhang, Z.: High-performance sparse linear algebra on HBM-equipped FPGAs using HLS: a case study on SPMV. In: Proceedings of the 2022 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, pp. 54–64 (2022)
4. Fowers, J., Ovtcharov, K., Strauss, K., Chung, E.S., Stitt, G.: A high memory bandwidth FPGA accelerator for sparse matrix-vector multiplication. In: FCCM 2014
5. Gautier, Q., Althoff, A., Meng, P., Kastner, R.: Spector: an OpenCL FPGA benchmark suite. In: FPT 2016