May 16, 2023 · This paper analyzes the performance of a gcForest model trained on the MNIST digit classification data set on a multi-core CPU based system.
This paper analyzes the performance of a gcForest model trained on the MNIST digit classification data set on a multi-core CPU based system.
We describe the existing computing devices for deep learning and analyze them in terms of different metrics, like performance, power and flexibility. Different ...
Performance Evaluation of gcForest inferencing on multi-core CPU and FPGA. ... Experience with PCIe streaming on FPGA for high throughput ML inferencing.
Performance Evaluation of gcForest inferencing on multi-core CPU and FPGA. Piyush Manavar. ,. Sharyu Vijay Mukhekar. ,. Manoj Nambiar. Proceedings of the Second ...
Performance Evaluation of gcForest inferencing on multi-core CPU and FPGA, [Paper ID: 28]. Authors: Piyush Manavar (TCS)*; Sharyu Vijay Mukhekar (TCS); Manoj ...
Performance Evaluation of gcForest inferencing on multi-core CPU and FPGA. 2022-10-12 | Conference paper. DOI: 10.1145/3564121.3564797. Contributors: Piyush ...
Performance Evaluation of gcForest inferencing on multi-core CPU and FPGAPiyush Manavar, Sharyu Vijay Mukhekar, Manoj Nambiar. aiml2 2022: [doi] · Automated ...
This paper presents an accelerator designed to optimize the execution of decision trees while reducing the energy consumption, implemented in an FPGA for ...
... multi-FPGA performance. Additionally, for the communication-centric ... Performance Evaluation of gcForest inferencing on multi-core CPU and FPGA.