Success-Case
Server ARM GIGABYTE Meningkatkan Pengembangan Solusi Lalu Lintas Cerdas Hingga 200%
Untuk mengirimkan pertanyaan: Hubungi bagian penjualan Ikuti GIGABYTE di Twitter: http://twitter.com/GIGABYTEServer Sebuah tim ilmuwan di NTU telah mengadopsi server G242-P32 GIGABYTE dan Arm HPC Developer Kit untuk menginkubasi "model arus lalu lintas presisi tinggi" - solusi lalu lintas cerdas yang dapat digunakan untuk menguji kendaraan otonom dan mengidentifikasi ruas jalan yang rawan kecelakaan untuk perbaikan. Solusi berbasis ARM menawarkan proyek peningkatan efisiensi 200% berkat arsitektur prosesor cloud-native yang "berbicara" dengan bahasa pemrograman yang sama dengan sensor di pinggir jalan, tingginya jumlah core CPU yang unggul dalam komputasi paralel, bersinergi dengan GPU yang memungkinkan komputasi heterogen, dan sertifikasi ISO yang membuat model yang dihasilkan mudah digunakan untuk pembuat mobil dan regulator pemerintah.
Manfaat #1: Prosesor ARM cloud-native berdasarkan arsitektur RISC
At the heart of the Arm HPC DevKit is the GIGABYTE G242-P32. This 2U GPU Server is powered by a single Ampere® Altra® Processor, which is a cloud-native ARM CPU that follows the same ISA as most mobile and edge devices. This drastically improves the efficiency of developing computer models or programs which can be used outside of conventional data centers—such as the roads and highways of Taiwan.
Manfaat #2: Jumlah core yang tinggi sangat ideal untuk komputasi paralel
Manfaat #3: GPU kuat dan memori bandwidth tinggi
Data collected by roadside sensors are sent back to the NTU lab for comparison, calibration, and compilation. Dr. Shih’s team employs a method known as heterogeneous computing to achieve optimal synergy between the CPU and the GPUs, so they can develop the “high-precision traffic flow model” more efficiently.
Manfaat #4: Kepatuhan pada ISO 26262 membuat solusi ARM lebih mudah diterapkan
Scalability
Edge Computing
HPC
Data Center
Machine Learning
Artificial Intelligence
GPU
Parallel Computing
ADAS
Point Cloud
Heterogeneous Computing
PCIe
GPGPU
Digital Twin
Core
CISC
RISC
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