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Cache and Memory
Published in Heqing Zhu, Data Plane Development Kit (DPDK), 2020
Intel® launched the Xeon Scalable Processor (SP) in 2017. The product code name is Skylake, which is designed for data center workload. The high-end Xeon SP can have up to 28 physical cores within each CPU, and the low-end processor can have six physical cores at a minimum. Figure 2.1 describes what’s inside of each physical core: It comes with L1 and L2 cache and memory channels. L1 cache has both data and instruction space with 32 KB each, and L2 cache size is about 1 MB.
A combined physical and DEM modelling approach to improve performance of rotary dryers by modifying flights design
Published in Drying Technology, 2021
Alireza Ghasemi, Alireza Hasankhoei, Gholamabbas Parsapour, Erfan Razi, Samad Banisi
The best and rather costly commercial CPUs for PCs typically have fewer than 30 cores (e.g., Intel Xeon Platinum 8173 M). It is, therefore, important to have access to thousands of processors to perform parallelization in a cost-effective way. One method is to use GPGPU (General-purpose computing on graphics processing units) technique. GPGPU is the use of a graphics processing unit (GPU), which usually handles computer graphics renders, to perform central processing unit (CPU) computational tasks. Typical GPUs include more than two thousand CUDA (Compute Unified Device Architecture) Cores (e.g., GTX Titan Xp includes 3840 CUDA Cores) allowing very efficient manipulation of large blocks of data. CUDA is a parallel computing platform and programing interface model developed by NVIDIA for general computing on GPUs. In GPU-accelerated applications, the sequential part of the workload runs on the CPU which is optimized for single-threaded performance while the compute intensive portion of the application runs on thousands of GPU cores in parallel.[45]