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Every year from April to October, the Sánchez family traveled—crowded in the back of trucks, camping in converted barns, tending and harvesting crops across the breadth of the United States. Although hoeing sugar beets with a short hoe was their specialty, they also picked oranges in California, apples in Washington, cucumbers in Michigan, onions and potatoes in Wisconsin, and tomatoes in Iowa. Winters they returned home to the Winter Garden region of South Texas. In 1951, Saúl Sánchez began to contribute to his family’s survival by helping to weed onions in Wind Lake, Wisconsin. He was eight years old. Rows of Memory tells his story and the story of his family and other migrant farm laborers like them, people who endured dangerous, dirty conditions and low pay, surviving because they took care of each other. Facing racism both on the road and at home, they lived a largely segregated life only occasionally breached by friendly employers. Despite starting school late and leaving early every year and having to learn English on the fly, young Saúl succeeded academically. At the same time that Mexican Americans in South Texas upended the Anglo-dominated social order by voting their own leaders into local government, he upended his family’s order by deciding to go to college. Like many migrant children, he knew that his decision to pursue an education meant he would no longer be able to help feed and clothe the rest of his family. Nevertheless, with his parents’ support, he went to college, graduating in 1967 and, after a final display of his skill with a short hoe for his new friends, abandoned migrant labor for teaching. In looking back at his youth, Sánchez invites us to appreciate the largely unrecognized and poorly rewarded strength and skill of the laborers who harvest the fruits and vegetables we eat. A first-person portrait of life on the bottom rung of the food system, this coming-of-age tale illuminates both the history of Latinos in the United States and the human consequences of industrial agriculture.
Tells the story fo Saul Sanchez and his family and other migrant farm laborers like them who endured dangerous, dirty conditions and low pay, surviving because they took care of each other. --p. 4 of cover.
Is your memory hierarchy stopping your microprocessor from performing at the high level it should be? Memory Systems: Cache, DRAM, Disk shows you how to resolve this problem. The book tells you everything you need to know about the logical design and operation, physical design and operation, performance characteristics and resulting design trade-offs, and the energy consumption of modern memory hierarchies. You learn how to to tackle the challenging optimization problems that result from the side-effects that can appear at any point in the entire hierarchy.As a result you will be able to design and emulate the entire memory hierarchy. - Understand all levels of the system hierarchy -Xcache, DRAM, and disk. - Evaluate the system-level effects of all design choices. - Model performance and energy consumption for each component in the memory hierarchy.
Provides a comprehensive, class-tested introduction to CUDA and GPU programming Covers CPU programming, parallellism, multi-threading, and other key concepts as a basis for understanding GPU programming Uses Nvidia's new platform based on Amazon EC2 and WebGPU Introduces GPU multi-threading and Global Memory, and the use of atomics and libraries on GPUs Includes example applications
Cost models are an essential part of database systems, as they are the basis of query performance optimization. Based on predictions made by cost models, the fastest query execution plan can be chosen and executed or algorithms can be tuned and optimised. In-memory databases shifts the focus from disk to main memory accesses and CPU costs, compared to disk based systems where input and output costs dominate the overall costs and other processing costs are often neglected. However, modelling memory accesses is fundamentally different and common models do not apply anymore. This work presents a detailed parameter evaluation for the plan operators scan with equality selection, scan with range selection, positional lookup and insert in in-memory column stores. Based on this evaluation, a cost model based on cache misses for estimating the runtime of the considered plan operators using different data structures is developed. Considered are uncompressed columns, bit compressed and dictionary encoded columns with sorted and unsorted dictionaries. Furthermore, tree indices on the columns and dictionaries are discussed. Finally, partitioned columns consisting of one partition with a sorted and one with an unsorted dictionary are investigated. New values are inserted in the unsorted dictionary partition and moved periodically by a merge process to the sorted partition. An efficient attribute merge algorithm is described, supporting the update performance required to run enterprise applications on read-optimised databases. Further, a memory traffic based cost model for the merge process is provided.
Process tabular data and build high-performance query engines on modern CPUs and GPUs using Apache Arrow, a standardized language-independent memory format, for optimal performance Key Features Learn about Apache Arrow's data types and interoperability with pandas and Parquet Work with Apache Arrow Flight RPC, Compute, and Dataset APIs to produce and consume tabular data Reviewed, contributed, and supported by Dremio, the co-creator of Apache Arrow Book DescriptionApache Arrow is designed to accelerate analytics and allow the exchange of data across big data systems easily. In-Memory Analytics with Apache Arrow begins with a quick overview of the Apache Arrow format, before moving on to helping you to understand Arrow’s versatility and benefits as you walk through a variety of real-world use cases. You'll cover key tasks such as enhancing data science workflows with Arrow, using Arrow and Apache Parquet with Apache Spark and Jupyter for better performance and hassle-free data translation, as well as working with Perspective, an open source interactive graphical and tabular analysis tool for browsers. As you advance, you'll explore the different data interchange and storage formats and become well-versed with the relationships between Arrow, Parquet, Feather, Protobuf, Flatbuffers, JSON, and CSV. In addition to understanding the basic structure of the Arrow Flight and Flight SQL protocols, you'll learn about Dremio’s usage of Apache Arrow to enhance SQL analytics and discover how Arrow can be used in web-based browser apps. Finally, you'll get to grips with the upcoming features of Arrow to help you stay ahead of the curve. By the end of this book, you will have all the building blocks to create useful, efficient, and powerful analytical services and utilities with Apache Arrow.What you will learn Use Apache Arrow libraries to access data files both locally and in the cloud Understand the zero-copy elements of the Apache Arrow format Improve read performance by memory-mapping files with Apache Arrow Produce or consume Apache Arrow data efficiently using a C API Use the Apache Arrow Compute APIs to perform complex operations Create Arrow Flight servers and clients for transferring data quickly Build the Arrow libraries locally and contribute back to the community Who this book is for This book is for developers, data analysts, and data scientists looking to explore the capabilities of Apache Arrow from the ground up. This book will also be useful for any engineers who are working on building utilities for data analytics and query engines, or otherwise working with tabular data, regardless of the programming language. Some familiarity with basic concepts of data analysis will help you to get the most out of this book but isn't required. Code examples are provided in the C++, Go, and Python programming languages.
A systematic description of microelectronic device design. Topics range from the basics to low-power and ultralow-voltage designs, subthreshold current reduction, memory subsystem designs for modern DRAMs, and various on-chip supply-voltage conversion techniques. It also covers process and device issues as well as design issues relating to systems, circuits, devices and processes, such as signal-to-noise and redundancy.