Our recent publication “Algorithmic Canonical Stratifications of Simplicial Complexes” proposes a new algorithm for data analysis that offers a topology-aware path towards explainable artificial intelligence. Despite (or, perhaps, due to) being mathematically rigorous, the text of the original work is virtually impenetrable for readers not familiar with the concepts, tools, and notation of topology. In order to convey our ideas to a wider audience, we present this supplemental introduction. Here, we summarize and explain in plain English the motivation, reasoning, and methods of our new topological data analysis algorithm that we term “canonical stratification”. Canonical-Stratification-for-Non-Mathematicians.pdf (38 KB) Table of Contents 1. Motivation 2. More on Canonical Stratification 3. Conclusion 1. Motivation Machine learning has advanced significantly in recent years and has proven itself to be a powerful and versatile tool in a variety of data-driven disciplines. Machine learning algorithms are now being used to make decisions in numerous areas
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This paper reviews the Intel® Advanced Vector Extensions 512 (Intel® AVX-512) instruction set and answers two critical questions: How do Intel® Xeon® Scalable processors based on the Skylake architecture (2017) compare to their predecessors based on Broadwell due to AVX-512? How are Intel Xeon processors based on Skylake different from their alternative, Intel® Xeon Phi™ processors with the Knights Landing architecture, which also feature AVX-512? We address these questions from the programmer’s perspective by demonstrating C language code of microkernels benefitting from AVX-512. For each example, we dig deeper and analyze the compilation practices, resultant assembly, and optimization reports. In addition to code studies, the paper contains performance measurements for a synthetic benchmark with guidelines on estimating peak performance. In conclusion, we outline the workloads and application domains that can benefit from the new features of AVX-512 instructions. Colfax-SKL-AVX512-Guide.pdf (524 KB) Table of Contents 1. Intel Advanced Vector Extensions 512
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Colfax Research offers computing technology services: Consulting We perform consulting on software porting, code modernization, and performance optimization. Anything from a telephone discussion to major code surgery. Commissioned Research Custom Cloud We can build, configure and host a shared computing resource for your training, computing or marketing purposes. Custom Training Who We Are We are a team of computing software professionals with scientific backgrounds. Colfax Research specializes in helping you adopt the ever more complex innovations in computing. Click to meet the team. Why Colfax Team. Our consultants and engineers have solid scientific foundation proven by Ph. D. degrees. This team has a thorough knowledge of the state-of-the-art methods and tools. It is made possible by years of experience in the field, constant training, and exposure to modern computing systems. Expertise. We have an established track record of high-quality research in computing software, system administration, and hardware configuration. Our domain of knowledge includes parallel processors,
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Browse our webinars and on-demand training on parallel programming, performance optimization for parallel processors, new technology and development tools. Some of our training programs feature remote access to training servers, original programming exercises and certificates of accomplishment. “HOW” Series: Deep Dive
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In this paper we will discuss the new HGST Shingled Magnetic Recording (SMR) drives, Ultrastar Archive Ha10, which offers storage capacities of 10 TB and beyond. With their high-density storage capacities, these drives are well suited for large “active archive” applications. In an active archive application, the data is frequently read but seldom modified. The SMR drives are host managed, meaning that the developer must manage the data storage on the drives. In this publication we introduce an open source library, libzbc, which was developed by the HGST team to assist developers who use SMR drives. The discussions cover topics from the very basics like opening a device, to more advanced topics like data padding. The goal of this paper is to give readers the necessary knowledge and tools to develop applications with libzbc. We will present an example, and then report several benchmarks of I/O operations on the HGST SMR drives, and discuss the SMR drive’s effectiveness as an active archive solution. Complete paper: HGST_Introduction_to_libzbc.pdf (361 KB) Sample codes
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Colfax offers consulting services for enterprises, research labs, and universities. Our consultants have deep knowledge of the available hardware solutions, software development tools and optimization practices, backed by years of experience in academic research and PhD degrees in computational disciplines. We can help you to: Optimize your existing application to take advantage of all levels of hardware parallelism, from vectors to cores to clusters and heterogeneous systems. Future-proof your application for upcoming innovations in computing solutions. Accelerate your application using coprocessor technologies. Investigate the potential system configurations that satisfy your cost, power and performance requirements. Take a deep dive to develop a novel approach to solving your computing problem. Educate your research and engineering specialists on the best known methods of modern computing. The expertise of our consultants is continuously refined and shared with the community in Colfax Research publications and intensive courses on the parallel programming of modern multi-core
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