| LDR | | 05728cmm u2200637Ki 4500 |
| 001 | | 000000316285 |
| 003 | | OCoLC |
| 005 | | 20230525180127 |
| 006 | | m d |
| 007 | | cr cnu---unuuu |
| 008 | | 190615s2019 enk o 001 0 eng d |
| 015 | |
▼a GBB9B4127
▼2 bnb |
| 016 | 7 |
▼a 019446072
▼2 Uk |
| 019 | |
▼a 1104698732
▼a 1108689990 |
| 020 | |
▼a 9781788292306
▼q electronic book |
| 020 | |
▼a 1788292308
▼q electronic book |
| 020 | |
▼z 9781788298117
▼q paperback |
| 035 | |
▼a 2158182
▼b (N$T) |
| 035 | |
▼a (OCoLC)1104712904
▼z (OCoLC)1104698732
▼z (OCoLC)1108689990 |
| 037 | |
▼a 1FB931C7-50F0-4997-A451-237F00B38033
▼b OverDrive, Inc.
▼n http://www.overdrive.com |
| 040 | |
▼a EBLCP
▼b eng
▼e rda
▼e pn
▼c EBLCP
▼d TEFOD
▼d UKMGB
▼d OCLCF
▼d OCLCQ
▼d YDX
▼d OCLCQ
▼d UKAHL
▼d OCLCQ
▼d N$T
▼d OCLCQ
▼d YDXIT
▼d 248032 |
| 049 | |
▼a MAIN |
| 050 | 4 |
▼a QA76.73.J85
▼b S36 2019 |
| 082 | 04 |
▼a 005.13/3
▼2 23 |
| 082 | 04 |
▼a 005.73
▼2 23 |
| 100 | 1 |
▼a Sengupta, Avik,
▼e author. |
| 245 | 10 |
▼a Julia high performance :
▼b optimizations, distributed computing, multithreading, and GPU programming with Julia 1.0 and beyond /
▼c Avik Sengupta. |
| 250 | |
▼a Second edition. |
| 260 | |
▼a Birmingham :
▼b Packt Publishing Ltd.,
▼c 2019. |
| 300 | |
▼a 1 online resource |
| 336 | |
▼a text
▼b txt
▼2 rdacontent |
| 337 | |
▼a computer
▼b c
▼2 rdamedia |
| 338 | |
▼a online resource
▼b cr
▼2 rdacarrier |
| 500 | |
▼a Port sharing for high-performance web serving |
| 500 | |
▼a Includes index. |
| 505 | 0 |
▼a Cover; Title Page; Copyright and Credits; Dedication; About Packt; Foreword; Contributors; Table of Contents; Preface; Chapter 1: Julia is Fast; Julia -- fast and dynamic; Designed for speed; JIT and LLVM; Types, type inference, and code specialization; How fast can Julia be?; Summary; Chapter 2: Analyzing Performance; Timing Julia functions; The @time macro; Other time macros; The Julia profiler; Using the profiler; ProfileView; Using Juno for profiling; Using TimerOutputs; Analyzing memory allocation; Using the memory allocation tracker; Statistically accurate benchmarking |
| 505 | 8 |
▼a Using BenchmarkTools.jlSummary; Chapter 3: Types, Type Inference, and Stability; The Julia type system; Using types; Multiple dispatch; Abstract types; Julia's type hierarchy; Composite and immutable types; Type parameters; Type inference; Type-stability; Definitions; Fixing type instability; The performance pitfalls; Identifying type stability; Loop variables; Kernel methods and function barriers; Types in storage locations; Arrays; Composite types; Parametric composite types; Summary; Chapter 4: Making Fast Function Calls; Using globals; The trouble with globals |
| 505 | 8 |
▼a Fixing performance issues with globalsInlining; Default inlining; Controlling inlining; Disabling inlining; Constant propagation; Using macros for performance; The Julia compilation process; Using macros; Evaluating a polynomial; Horner's method; The Horner macro; Generated functions; Using generated functions; Using generated functions for performance; Using keyword arguments; Summary; Chapter 5: Fast Numbers; Numbers in Julia, their layout, and storage; Integers; Integer overflow; BigInt; The floating point; Floating point accuracy; Unsigned integers; Trading performance for accuracy |
| 505 | 8 |
▼a The @fastmath macroThe K-B-N summation; Subnormal numbers; Subnormal numbers to zero; Summary; Chapter 6: Using Arrays; Array internals in Julia; Array representation and storage; Column-wise storage; Adjoints; Array initialization; Bounds checking; Removing the cost of bounds checking; Configuring bound checks at startup; Allocations and in-place operations; Preallocating function output; sizehint!; Mutating functions; Broadcasting; Array views; SIMD parallelization (AVX2, AVX512); SIMD.jl; Specialized array types; Static arrays; Structs of arrays; Yeppp! |
| 505 | 8 |
▼a Writing generic library functions with arraysSummary; Chapter 7: Accelerating Code with the GPU; Technical requirements; Getting started with GPUs; CUDA and Julia; CuArrays; Monte Carlo simulation on the GPU; Writing your own kernels; Measuring GPU performance; Performance tips; Scalar iteration; Combining kernels; Processing more data; Deep learning on the GPU; ArrayFire; Summary; Chapter 8: Concurrent Programming with Tasks; Tasks; Using tasks; The task life cycle; task_local_storage; Communicating between tasks; Task iteration; High-performance I/O |
| 520 | |
▼a Julia is a high-level, high-performance dynamic programming language for numerical computing. This book will help you understand the performance characteristics of your Julia programs and achieve near-C levels of performance in Julia. |
| 588 | |
▼a Description based on online resource; title from digital title page (viewed on August 03, 2020). |
| 590 | |
▼a Master record variable field(s) change: 050, 082 |
| 650 | 0 |
▼a Julia (Computer program language) |
| 650 | 0 |
▼a Application software
▼x Development. |
| 650 | 7 |
▼a Application software
▼x Development.
▼2 fast
▼0 (OCoLC)fst00811707 |
| 650 | 7 |
▼a Julia (Computer program language)
▼2 fast
▼0 (OCoLC)fst01938397 |
| 655 | 4 |
▼a Electronic books. |
| 700 | 1 |
▼a Edelman, Alan. |
| 776 | 08 |
▼i Print version:
▼a Sengupta, Avik.
▼t Julia High Performance : Optimizations, Distributed Computing, Multithreading, and GPU Programming with Julia 1. 0 and Beyond, 2nd Edition.
▼d Birmingham : Packt Publishing, Limited, 짤2019
▼z 9781788298117 |
| 856 | 40 |
▼3 EBSCOhost
▼u http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=2158182 |
| 938 | |
▼a Askews and Holts Library Services
▼b ASKH
▼n BDZ0040173887 |
| 938 | |
▼a ProQuest Ebook Central
▼b EBLB
▼n EBL5788735 |
| 938 | |
▼a EBSCOhost
▼b EBSC
▼n 2158182 |
| 938 | |
▼a YBP Library Services
▼b YANK
▼n 300607329 |
| 990 | |
▼a 관리자 |
| 994 | |
▼a 92
▼b N$T |