CPU vs GPU Comparison
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CPUs have multiple cores and are suited for a variety of tasks requiring low latency, while GPUs have many smaller cores optimized for parallel processing. GPUs can perform thousands of basic operations simultaneously. Though CPUs and GPUs both process data, CPUs are designed for serial tasks and general computing while GPUs are specialized for graphics processing and parallel tasks like those in AI and supercomputing. Efficient parallel processing is what allows GPUs to outperform CPUs for certain applications.
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CPU vs. GPU presentation
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Recommended
CPU vs. GPU presentation
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This document describes the design and implementation of a 32-bit RISC processor intended for low power applications. The processor was developed using VHDL and implemented on a Xilinx Spartan-3E FPGA. It has a simple instruction set, program and data memories, general purpose registers, and an ALU. The processor follows a multi-cycle execution model. Simulation results show the processor executing instructions correctly in a single clock cycle, as intended for a RISC design. Power analysis shows the proposed RISC architecture consumes 132mW of power, half of previous designs, demonstrating its efficiency for low power applications.
Module 1 unit 3
The document provides information about processors and CPU terminology. It defines terms like data bus, address bus, registers, instruction set, and cache. It describes how CPUs work using transistors and how manufacturers like Intel and AMD make CPUs. It outlines the components of CPUs like execution cores, arithmetic logic units, and memory controllers. The document provides a timeline of CPUs from the 1970s to recent years to show advances in processing power and core counts.
Computing power technology – an overview.pdf
Computing power technology refers to the capacity of a computer or computer system to execute complex computations and data processing tasks. The number of calculations or operations a computer or system can perform per second is one common way to express processing speed.
For more info you can visit: https://www.temok.com/blog/computing-power-technology-an-overview/
Graphics Processing Unit: An Introduction
Graphics Processing Unit GPU is a processor or electronic chip for graphics. GPUs are massively parallel processors used widely used for 3D graphic and many non graphic applications. As the demand for graphics applications increases, GPU has become indispensable. The use of GPUs has now matured to a point where there are countless industrial applications. This paper provides a brief introduction on GPUs, their properties, and their applications. Matthew N. O. Sadiku | Adedamola A. Omotoso | Sarhan M. Musa "Graphics Processing Unit: An Introduction" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-1 , December 2019, URL: https://www.ijtsrd.com/papers/ijtsrd29647.pdf Paper URL: https://www.ijtsrd.com/engineering/electrical-engineering/29647/graphics-processing-unit-an-introduction/matthew-n-o-sadiku
Processors
This Presentation gives brief information about the microprocessors which are used in computers as well as mobile phones. Also it includes information related to how the processors work, The terms associated with it and top manufacturing companies along with it's price range.
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The document summarizes a technical seminar on processors presented by Bharat Kumar Rajak. It discusses the evolution of processors from early transistor-based designs to modern multi-core CPUs. It covers key topics like processor architecture, types of processors including RISC and CISC, applications, and future directions. Examples are provided to illustrate concepts like single-core, dual-core, and multi-core processor designs as well as cache memory and clock speed. The seminar aims to provide an overview of processors, their history, workings and importance in computers and other electronics.
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A SURVEY ON GPU SYSTEM CONSIDERING ITS PERFORMANCE ON DIFFERENT APPLICATIONS
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Eventual consistency vs Strong consistency what is the difference
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Batch Processing vs Stream Processing Difference
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Difference Program vs Process vs Thread
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Measures in SQL (SIGMOD 2024, Santiago, Chile)
SQL has attained widespread adoption, but Business Intelligence tools still use their own higher level languages based upon a multidimensional paradigm. Composable calculations are what is missing from SQL, and we propose a new kind of column, called a measure, that attaches a calculation to a table. Like regular tables, tables with measures are composable and closed when used in queries.
SQL-with-measures has the power, conciseness and reusability of multidimensional languages but retains SQL semantics. Measure invocations can be expanded in place to simple, clear SQL.
To define the evaluation semantics for measures, we introduce context-sensitive expressions (a way to evaluate multidimensional expressions that is consistent with existing SQL semantics), a concept called evaluation context, and several operations for setting and modifying the evaluation context.
A talk at SIGMOD, June 9–15, 2024, Santiago, Chile
Authors: Julian Hyde (Google) and John Fremlin (Google)
https://doi.org/10.1145/3626246.3653374
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CPU vs GPU Comparison
- 2. What Is a CPU? Constructed from millions of transistors, the CPU can have multiple processing cores and is commonly referred to as the brain of the computer. It is essential to all modern computing systems as it executes the commands and processes needed for your computer and operating system. The CPU is also important in determining how fast programs can run, from surfing the web to building spreadsheets.
- 3. What Is a GPU? The GPU is a processor that is made up of many smaller and more specialized cores. By working together, the cores deliver massive performance when a processing task can be divided up and processed across many cores. The clock speed of a GPU may be lower than modern CPUs (normally in the range of 500-800 MHz), but the number of cores on each chip is much denser. This is one of the most distinct differences between a graphics card vs CPU. This allows a GPU to perform a lot of basic tasks at the same time.
- 5. Difference Between a CPU and GPU? CPUs and GPUs have a lot in common. Both are critical computing engines. Both are silicon-based microprocessors. And both handle data. But CPUs and GPUs have different architectures and are built for different purposes. The CPU is suited to a wide variety of workloads, especially those for which latency or per-core performance are important. A powerful execution engine, the CPU focuses its smaller number of cores on individual tasks and on getting things done quickly. This makes it uniquely well equipped for jobs ranging from serial computing to running
- 6. GPUs: Key to AI, Computer Vision, Supercomputing and More Over the past decade that’s proven key to a growing range of applications. GPUs perform much more work for every unit of energy than CPUs. That makes them key to supercomputers that would otherwise push past the limits of today’s electrical grids. In AI, GPUs have become key to a technology called “deep learning.” Deep learning pours vast quantities of data through neural networks, training them to perform tasks too complicated
- 9. Central Processing Unit Graphics Processing Unit Several cores Many cores Low latency High throughput Good for serial processing Good for parallel processing Can do a handful of operations at once Can do thousands of operations at once
- 11. Why Have Two Different Processor Types? Everyone is somewhat familiar with CPUs. Known as the “brain” of a computer, they are composed of millions upon millions of tiny transistors with multiple “cores.” It is critical for handling the main processing functions of a computer. Actions like running the operating system and applications would not be possible without it. The CPU is also what determines the general speed of a computer. GPUs are more specialized in nature. Originally designed to help with 3D rendering, they can do more processing in parallel. This is perfect for use in graphic-intensive applications that rely on displaying dynamic content for gaming, or compressing/decompressing streaming videos. GPUs are also being used in many other areas beyond rendering and image processing, like Artificial Intelligence and Bitcoin mining. The main difference between a CPU and a GPU is how they process the instructions given to them. In human terms, you could say that a CPU is the master of taking on one task at a time, whereas a GPU can take on many tasks at once. While there are some that work better doing things in sequential order, others can multitask.
- 12. Summary The CPU is responsible for the serial processing while the GPU is responsible for the parallel processing of tasks. Thus for the high performance of the computer both CPU and GPU are required. This will make parallel portions of code run on GPU and serial portions on the CPU. If seen individually both have their own limitations. A CPU has heavy-weight instruction sets, slow switch latency, and defy Moore’s law. While GPU has less powerful cores, can focus on only one task at a time, has limited APIs.
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