Minor fixes in readme

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tevador 2019-05-15 14:13:49 +02:00
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# RandomX
RandomX is a proof-of-work (PoW) algorithm that is optimized for general-purpose CPUs. RandomX uses random code execution (hence the name) together with several memory-hard techniques to achieve the following goals:
* Prevent the development of a single-chip [ASIC](https://en.wikipedia.org/wiki/Application-specific_integrated_circuit)
* Minimize the efficiency advantage of specialized hardware compared to a general-purpose CPU
RandomX is a proof-of-work (PoW) algorithm that is optimized for general-purpose CPUs. RandomX uses random code execution (hence the name) together with several memory-hard techniques to minimize the efficiency advantage of specialized hardware.
## Overview
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RandomX is written in C++11 and builds a static library with a C API provided by header file [randomx.h](src/randomx.h). Minimal API usage example is provided in [api-example1.c](src/tests/api-example1.c). The reference code includes a `benchmark` executable for testing.
### Ubuntu/Debian
### Linux
Build dependencies: `make` and `gcc` (minimum version 4.8, but version 7+ is recommended).
@ -57,7 +54,7 @@ Preliminary performance of selected CPUs using the optimal number of threads (T)
|CPU|RAM|OS|AES|Fast mode|Light mode|
|---|---|--|---|---------|--------------|
AMD Ryzen 7 1700|16 GB DDR4|Ubuntu 16.04|hardware|4090 H/s (8T)|620 H/s (16T)|
AMD Ryzen 7 1700|16 GB DDR4|Ubuntu 16.04|hardware|4100 H/s (8T)|620 H/s (16T)|
Intel Core i7-8550U|16 GB DDR4|Windows 10|hardware|1700 H/s (4T)|350 H/s (8T)|
Intel Core i3-3220|2 GB DDR3|Ubuntu 16.04|software|-|145 H/s (4T)|
Raspberry Pi 3|1 GB DDR2|Ubuntu 16.04|software|-|2.0 H/s (4T) †|
@ -80,9 +77,9 @@ Efficient mining requires more than 2 GiB of memory, which is difficult to hide
RandomX uses only operations that are guaranteed to give correctly rounded results by the [IEEE 754](https://en.wikipedia.org/wiki/IEEE_754) standard: addition, subtraction, multiplication, division and square root. Special care is taken to avoid corner cases such as NaN values or denormals.
The reference implementation has been validated on the following platforms:
* x86+SSE2 (32-bit, little-endian)
* x86 (32-bit, little-endian)
* x86-64 (64-bit, little-endian)
* ARMv7+NEON (32-bit, little-endian)
* ARMv7+VFPv3 (32-bit, little-endian)
* ARMv8 (64-bit, little-endian)
* PPC64 (64-bit, big-endian)