About Cabling Installation & Maintenance

Our mission: Bringing practical business and technical intelligence to today's structured cabling professionals

For more than 30 years, Cabling Installation & Maintenance has provided useful, practical information to professionals responsible for the specification, design, installation and management of structured cabling systems serving enterprise, data center and other environments. These professionals are challenged to stay informed of constantly evolving standards, system-design and installation approaches, product and system capabilities, technologies, as well as applications that rely on high-performance structured cabling systems. Our editors synthesize these complex issues into multiple information products. This portfolio of information products provides concrete detail that improves the efficiency of day-to-day operations, and equips cabling professionals with the perspective that enables strategic planning for networks’ optimum long-term performance.

Throughout our annual magazine, weekly email newsletters and 24/7/365 website, Cabling Installation & Maintenance digs into the essential topics our audience focuses on.

  • Design, Installation and Testing: We explain the bottom-up design of cabling systems, from case histories of actual projects to solutions for specific problems or aspects of the design process. We also look at specific installations using a case-history approach to highlight challenging problems, solutions and unique features. Additionally, we examine evolving test-and-measurement technologies and techniques designed to address the standards-governed and practical-use performance requirements of cabling systems.
  • Technology: We evaluate product innovations and technology trends as they impact a particular product class through interviews with manufacturers, installers and users, as well as contributed articles from subject-matter experts.
  • Data Center: Cabling Installation & Maintenance takes an in-depth look at design and installation workmanship issues as well as the unique technology being deployed specifically for data centers.
  • Physical Security: Focusing on the areas in which security and IT—and the infrastructure for both—interlock and overlap, we pay specific attention to Internet Protocol’s influence over the development of security applications.
  • Standards: Tracking the activities of North American and international standards-making organizations, we provide updates on specifications that are in-progress, looking forward to how they will affect cabling-system design and installation. We also produce articles explaining the practical aspects of designing and installing cabling systems in accordance with the specifications of established standards.

Cabling Installation & Maintenance is published by Endeavor Business Media, a division of EndeavorB2B.

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Patrick McLaughlin

Serena Aburahma

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MLCommons Introduces MLPerf Client v0.5

A New Benchmark for Consumer AI Performance

MLCommons®, the leading open engineering consortium dedicated to advancing machine learning (ML), is excited to announce the public release of the MLPerf® Client v0.5 benchmark. This benchmark sets a new standard for evaluating consumer AI performance, enabling users, press, and the industry to measure how effectively laptops, desktops, and workstations can run cutting-edge large language models (LLMs).

A Collaborative Effort by Industry Leaders

MLPerf Client represents a collaboration among technology leaders, including AMD, Intel, Microsoft, NVIDIA, Qualcomm Technologies, Inc., and top PC OEMs. These stakeholders have pooled resources and expertise to create a standardized benchmark, offering new insight into performance on key consumer AI workloads.

“MLPerf Client is a pivotal step forward in measuring consumer AI PC performance, bringing together industry heavyweights to set a new standard for evaluating generative AI applications on personal computers,” said David Kanter, Head of MLPerf at MLCommons.

Key Features of the MLPerf Client v0.5 benchmark:

  • AI model: The benchmark’s tests are based on Meta's Llama 2 7B large language model, optimized for reduced memory and computational requirements via 4-bit integer quantization.
  • Tests and metrics: Includes four AI tasks—content generation, creative writing, and text summarization of two different document lengths—evaluated using familiar metrics like time-to-first-token (TTFT) and tokens-per-second (TPS).
  • Hardware optimization: Supports hardware-accelerated execution on integrated and discrete GPUs via two distinct paths: ONNX Runtime GenAI and Intel OpenVINO.
  • Platform support: This initial release supports Windows 11 on x86-64 systems, with future updates planned for Windows on Arm and macOS.
  • Freely accessible: The benchmark is freely downloadable from MLCommons.org, empowering anyone to measure AI performance on supported systems.

Future Development

While version 0.5 marks the benchmark's debut, MLCommons plans to expand its capabilities in future releases, including support for additional hardware acceleration paths and a broader set of test scenarios incorporating a range of AI models.

Availability

The MLPerf Client v0.5 benchmark is available for download now from MLCommons. See the website for additional details on the benchmark’s hardware and software support requirements.

About MLCommons

MLCommons is the world leader in building benchmarks for AI. It is an open engineering consortium with a mission to make AI better for everyone through benchmarks and data. The foundation for MLCommons began with the MLPerf benchmarks in 2018, which rapidly scaled as a set of industry metrics to measure machine learning performance and promote transparency of machine learning techniques. In collaboration with its 125+ members, global technology providers, academics, and researchers, MLCommons is focused on collaborative engineering work that builds tools for the entire AI industry through benchmarks and metrics, public datasets, and measurements for AI risk and reliability.

For more information and details on becoming a member, please visit MLCommons.org or contact participation@mlcommons.org.

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