Research Article

Performance Evaluation of Deep Learning Algorithm Using High-End Media Processing Board in Real-Time Environment

Table 2

Compares various Jetson embedded boards in terms of performance features taken from [17] adapted from [39].

Comparison of different NVIDIA Jetson boards
CharacteristicsJetson NanoJetson TX1Jetson TX2Jetson Xavier NXJetson AGX Xavier

CPU (central processing unit)Quad-core ARM A57, 1.43 GHzQuad-core A57 processorQuad-core ARM A57 BD Dual-core Denver 2 64-bit CPU6-core NVIDIA Carmel ARM 64-bit CPU 6 MB L2+4 MB L38-Core ARM 64-bit CPU, 8 MB L2+4 MB L3

GPU128 core NVIDIA MaxwellNVIDIA Maxwell GPU with 256 CUDA coresN Pascal with 256 NVIDIA CUDA coresNVIDIA Volta, 384 CUDA cores, and 48 tensor cores512-CUDA cores and 64 tensor cores

DL accelerator (deep learning accelerator)NoneNoneNone2× NVDLA engines(2×) NVDLA engine

Memory2 GB 64-bit LPDDR44 GB LPDDR4 memory8 GB 128-bit LPDDR48 GB 128-bit LPDDR4× 59.7 GB/s16 GB 256-bit LPDDR4x

StorageMicroSD16 GB eMMC 5.132 GB eMMC 5.1MicroSD32 GB eMMC 5.1

Video encoder4Kp30-4× 720p30 (H.264/H.265)4 K at a rate of 30 at a rate of 30 (HEVC), 20× 1080p30 (H.264) at a rate of 60 (HEVC)

Video decoder4Kp60-2×18× 720p30 (H.264/H.265)4 K rate of 30 at 30, 12-bit support K30-6× 4 K60 1080p 30 (H.265)
22× 1080p30 (H.264)
at a rate of 30 12-bit support

Cost$99$520$599$399$699