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Designing the Switch/Router
Published in James Aweya, Designing Switch/Routers, 2023
The CPU runs at a specified internal clock speed or frequency (usually measured in megahertz (MHz) or gigahertz (GHz)) which represents the number of cycles per second it can execute instructions. This determines the speed at which the CPU executes instructions of various types. The motherboard on which the CPU resides provides an external clock which the CPU uses to determine its own operational speeds. The external clock is different from the CPU clock speed (its internal frequency). The system uses a clock multiplier (CPU multiplier or CPU Clock Ratio) to set the ratio of the internal CPU clock speed to the externally supplied clock. The internal CPU speed is obtained by multiplying the externally supplied clock speed by the clock multiplier.
Achieving Scalability in the 5G-Enabled Internet of Things
Published in Yulei Wu, Haojun Huang, Cheng-Xiang Wang, Yi Pan, 5G-Enabled Internet of Things, 2019
Fuchun Joseph Lin, David de la Bastida
where TDP is the microprocessor’s Thermal Design Power, a reference measurement of CPU running in normal conditions and given by the manufacturer. For our particular testbed, TDP is 80 W. In addition, K is the common power consumption of memory modules, typically 3 W for DDR3 memory cards. CPU% and Memory% are the average CPU and memory measurements, respectively, on each host system. Figure 5.21 shows that there is 16.5%, 9%, 12.5% and 12.7% less power consumption for smart meter, eHealth, Bluetooth tags and video, respectively. This is due to the fact that the system is able to handle a larger number of requests during the same period of time with network slicing enabled, thus a lower power consumption per request can be achieved.
How to Untangle Complex Systems?
Published in Pier Luigi Gentili, Untangling Complex Systems, 2018
where M is the number of switches working with the clock frequency ν of the microprocessor (Cavin et al. 2012). The computational power of a CPU, measured in the number of instructions per second, is directly proportional to β. Therefore, it is evident that for larger computational power, it is important to increase not only M but also ν. Researchers have found that a silicon CPU can work at most at a frequency of 4 gigahertz without melting from excessive heat production. To overcome this hurdle, it is necessary to introduce either an effective cooling system or multi-core CPUs. A multi-core CPU is a single computing element with two or more processors, called “cores,” which work in parallel. The speed-up (Sp) of the calculations is described by the Amdahl’s law (Amdahl 1967): [] Sp=1(1−P)+PN
Accelerating Dense Matrix Computations with Effective Workload Partitioning on Heterogeneous Architectures
Published in IETE Journal of Research, 2019
Mohsin Khan, Waseem Ahmed, Touseef M. Golandaz
A CPU generally contains multiple cores to perform tasks. Each core can work in parallel and perform different tasks. CPU also has cache memory which helps to increase performance by optimizing the locality. CPU acts like a host processor for GPUs, since GPUs cannot work in standalone mode. A GPU is a processor dedicated solely to graphical processing operations. It is a single chip processor which contains many cores, but these cores are small in size and runs at low speed as compared to CPU cores. Numerous calculations can be processed simultaneously on a GPU, since it has a very high degree of data parallelism. GPU is used as co-processor on the computer system and has its own memory that processes many threads. A GPU can be used for General Purpose Processing (GPGPU) [1, 2]. The primary purpose behind the accomplishment of general purpose processing on GPU was because of the ease of programming given by the parallel programming model such as CUDA [3], OpenCL [4], and so on. In CUDA programming model, the application developer maps the application's computation to GPU and all this is initiated by the program running on CPU.
Flux Region Assignment Method Using Ray Trace Information for the Method of Characteristics to Improve Cache Efficiency
Published in Nuclear Science and Engineering, 2018
Akio Yamamoto, Akinori Giho, Tomohiro Endo
In today’s computers, the clock frequency of the CPU reaches gigahertz, implying memory access speed is much slower than the processing speed of the CPU and becomes a crucial bottleneck for the overall computational performance. In order to mitigate the latency of memory access, the cache memory is utilized. The cache memory is physically placed near the CPU and its access speed is much faster than that of main memory, though its size is limited. In many CPU architectures, the multilevel cache is implemented. For example, cache sizes are 32 KB + 32 KB, 256 KB, and 8 MB for L1, L2, and L3 caches, respectively, which are significantly smaller than that of main memory.
Cache performance of NV-STT-MRAM with scale effect and comparison with SRAM
Published in International Journal of Electronics, 2022
Zitong Zhang, Wenjie Wang, Pingping Yu, Yanfeng Jiang
Based on the traditional architecture of the CPU, the cache structure is used to connect the CPU and the main memory for the data exchange. The existence of the cache can diminish the unbalanced speeds between the CPU and the memory. The CPU fetches the instructions from main memory, while its speed depending on fetching speed. Cache memory is a kind of very high-speed memory that is placed between the CPU and main memory to solve the problem of speed mismatch in different structures. The schematic of the CPU system is shown in Figure 1.