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Solution tests mobile and 5G private network performance using millions of devices to establish simultaneous voice, video and web sessions in real-world scenarios
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Supports smart manufacturing, smart grid and many other industry scenarios that require connecting millions of low-latency, high-bandwidth devices
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New method uses realistically generated traffic to reveal true CPU power and scalability, observe bandwidth requirements, and enable optimal network configurations
Keysight Technologies, Inc. has developed a new benchmarking methodology using the 4th Generation AMD EPYC™ CPU from Advanced Micro Devices, Inc. that can help high-speed digital design companies, network equipment manufacturers and data center operators reevaluate system performance.
Keysight Technologies and AMD Collaborate to Break Through Technology Barriers and Redefine Cloud and Edge Infrastructure Performance Benchmarks
As part of automation and digital transformation strategies, mobile and 5G private network deployments are expected to grow rapidly in many industries. This diverse industry use case requires a common computing architecture that can simultaneously support millions of low-latency, high-bandwidth devices and multifaceted workload profiles. Given this transformation, the industry needs to ensure performance in a variety of industry use cases through comprehensive infrastructure benchmarking.
To provide realistic performance benchmarks, Keysight Technologies and AMD have collaborated to develop an integrated test case methodology that takes into account the processing power of central processing units (CPUs). The new methodology uses realistic traffic simulation to enable data center operators to fully exploit the performance of their selected CPUs and characterize the performance of multiple vectors while meeting bandwidth requirements. The methodology developed by the two companies deploys Keysight software tools on AMD DPYC™ processors to run staged test cases at scale using realistic traffic.
This test case method has the following characteristics:
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Infrastructure Scalability - In environments such as smart grids and smart manufacturing, smooth and reliable operation requires handling millions of devices running simultaneously. Traditional benchmarks often ignore the capacity of the CPU and its ability to handle high concurrent loads because this capability is masked by the bandwidth limitations of the network. The new benchmark method is designed to reveal the true CPU power and scalability in such environments.
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Reality – Mobile and 5G private networks can support specialized areas such as vision-based smart manufacturing, extended reality (XR), and retail workflows. Testing the infrastructure’s ability to handle real-world application, voice, and video traffic is critical. The new benchmark focuses on reproducing batch activities, such as millions of devices establishing new sessions, or extremely realistic scenarios such as users initiating voice, video, and web calls. With this deep insight into real-world capabilities, data center operators can accurately configure their infrastructure.
"5G mobile network operators around the world are under tremendous pressure to meet bandwidth demands," said Raghu Nambiar, vice president of Data Center Ecosystem and Solutions at AMD . "As data traffic continues to grow, scalable and proven benchmarking solutions are needed to accurately measure the user experience. Our collaboration with Keysight Technologies has proven that the AMD EPYC CPU has the parallel processing capabilities to benchmark performance in high data traffic scenarios."
"Data center operators have difficulty properly designing and deploying their compute infrastructure using only single-dimensional benchmarks such as throughput," said Ram Periakaruppan, vice president and general manager of Keysight's Network Test and Security Solutions Group . "Modern mobile and 5G private networks require a new performance benchmarking approach that fully exploits the power of AMD's Zen 4 chiplet architecture and meets the complex demands of private networks."
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