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Clojure High Performance Programming, Second Edition

Clojure High Performance Programming, Second Edition - Second Edition

By : Kumar
4.4 (5)
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Clojure High Performance Programming, Second Edition

Clojure High Performance Programming, Second Edition

4.4 (5)
By: Kumar

Overview of this book

Clojure treats code as data and has a macro system. It focuses on programming with immutable values and explicit progression-of-time constructs, which are intended to facilitate the development of more robust programs, particularly multithreaded ones. It is built with performance, pragmatism, and simplicity in mind. Like most general purpose languages, various Clojure features have different performance characteristics that one should know in order to write high performance code. This book shows you how to evaluate the performance implications of various Clojure abstractions, discover their underpinnings, and apply the right approach for optimum performance in real-world programs. It starts by helping you classify various use cases and the need for them with respect to performance and analysis of various performance aspects. You will also learn the performance vocabulary that experts use throughout the world and discover various Clojure data structures, abstractions, and their performance characteristics. Further, the book will guide you through enhancing performance by using Java interoperability and JVM-specific features from Clojure. It also highlights the importance of using the right concurrent data structure and Java concurrency abstractions. This book also sheds light on performance metrics for measuring, how to measure, and how to visualize and monitor the collected data. At the end of the book, you will learn to run a performance profiler, identify bottlenecks, tune performance, and refactor code to get a better performance.
Table of Contents (10 chapters)
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9
Index

The latency numbers that every programmer should know

Hardware and software have progressed over the years. Latencies for various operations put things in perspective. The latency numbers for the year 2015, reproduced with the permission of Aurojit Panda and Colin Scott of Berkeley University (http://www.eecs.berkeley.edu/~rcs/research/interactive_latency.html). Latency numbers that every programmer should know are as shown in the following table:

Operation

Time taken as of 2015

L1 cache reference

1ns (nano second)

Branch mispredict

3 ns

L2 cache reference

4 ns

Mutex lock/unlock

17 ns

Compress 1KB with Zippy

(Zippy/Snappy: http://code.google.com/p/snappy/)

2μs (1000 ns = 1μs: micro second)

Send 2000 bytes over the commodity network

200ns (that is, 0.2μs)

SSD random read

16 μs

Round-trip in the same datacenter

500 μs

Read 1,000,000 bytes sequentially from SSD

200 μs

Disk seek

4 ms (1000 μs = 1 ms)

Read 1,000,000 bytes sequentially from disk

2 ms

Packet roundtrip CA to Netherlands

150 ms

The preceding table shows the operations in a computer vis-a-vis the latency incurred due to the operation. When a CPU core processes some data in a CPU register, it may take a few CPU cycles (for reference, a 3 GHz CPU runs 3000 cycles per nanosecond), but the moment it has to fall back on L1 or L2 cache, the latency becomes thousands of times slower. The preceding table does not show main memory access latency, which is roughly 100 ns (it varies, based on the access pattern)—about 25 times slower than the L2 cache.

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