Hubwiz Ethereum
Publish: 2021-05-16 07:58:36
1. How to run Ethereum source code go Ethereum
install MIPS based Linux header file
$CD $prjroot / kernel
$tar - xjvf linux-2.6.38. Tar. Bz2
$CD linux-2.6.38
create an include folder under the specified path to store related header files< br />$ mkdir -p $TARGET_ Prefix / include
ensures that the Linux source code is clean
$make mrproper
generates the required header file< br />$ make ARCH=mips headers_ check
$ make ARCH=mips INSTALL_ HDR_ PATH=dest headers_ Install
all the files in dest folder to the specified include folder< br />$ cp -rv dest/include/* $TARGET_ Prefix / include
delete dest folder at last
$RM - RF dest
$LS - L $target_ PREFIX/include
install MIPS based Linux header file
$CD $prjroot / kernel
$tar - xjvf linux-2.6.38. Tar. Bz2
$CD linux-2.6.38
create an include folder under the specified path to store related header files< br />$ mkdir -p $TARGET_ Prefix / include
ensures that the Linux source code is clean
$make mrproper
generates the required header file< br />$ make ARCH=mips headers_ check
$ make ARCH=mips INSTALL_ HDR_ PATH=dest headers_ Install
all the files in dest folder to the specified include folder< br />$ cp -rv dest/include/* $TARGET_ Prefix / include
delete dest folder at last
$RM - RF dest
$LS - L $target_ PREFIX/include
2. Ethereum is an open source public blockchain platform with smart contract function. Ethernet provides decentralized virtual machine to process point-to-point contract through its special cryptocurrency
3. In order to meet the rapid growth of Google's data processing needs, Google has designed and implemented the Google File System (GFS). GFS has many of the same goals as distributed file systems in the past, such as performance, scalability, reliability, and availability. However, its design is also influenced by Google's application load and technology environment. It is mainly reflected in the following four aspects:
1. Node failure in a cluster is a normal rather than an exception. Due to the huge number of nodes involved in the operation and processing, thousands of nodes are usually used for common calculation, so there are always nodes in failure state at any time. It is necessary to monitor the dynamic operation of the system, detect errors, and integrate fault tolerance and automatic recovery system into the system through software program mole
2. The concept of file size in Google system is different from that in common file system. File size is usually measured in G bytes. In addition, the meaning of files in the file system is different from that of common files. A large file may contain a large number of small files in the common sense. Therefore, design expectations and parameters, such as I / O operation and block size, need to be reconsidered
3. The file read-write mode in Google file system is different from that in traditional file system. In Google Applications (such as search), the modification of most files does not cover the original data, but adds new data at the end of the file. Random writing to files is almost nonexistent. For the access mode of such huge files, the client loses the significance of data block cache, and the append operation becomes performance optimization and atomicity (a transaction is regarded as a program). It is either fully implemented or not implemented at all
4. Some specific operations of the file system are no longer transparent and need the assistance of the application program. The collaborative design of the application program and the file system API improves the flexibility of the whole system. For example, the requirement of GFS consistency model is relaxed, so that the design of file system is greatly simplified without increasing the burden of application. Atomic appending operation is also introced, so that when multiple clients are appending at the same time, there is no need for additional synchronization operation
in short, GFS is designed for the Google App itself. It is said that Google has deployed many GFS clusters. Some clusters have more than 1000 storage nodes and more than 300t of hard disk space, which are frequently accessed by hundreds of clients on different machines.
1. Node failure in a cluster is a normal rather than an exception. Due to the huge number of nodes involved in the operation and processing, thousands of nodes are usually used for common calculation, so there are always nodes in failure state at any time. It is necessary to monitor the dynamic operation of the system, detect errors, and integrate fault tolerance and automatic recovery system into the system through software program mole
2. The concept of file size in Google system is different from that in common file system. File size is usually measured in G bytes. In addition, the meaning of files in the file system is different from that of common files. A large file may contain a large number of small files in the common sense. Therefore, design expectations and parameters, such as I / O operation and block size, need to be reconsidered
3. The file read-write mode in Google file system is different from that in traditional file system. In Google Applications (such as search), the modification of most files does not cover the original data, but adds new data at the end of the file. Random writing to files is almost nonexistent. For the access mode of such huge files, the client loses the significance of data block cache, and the append operation becomes performance optimization and atomicity (a transaction is regarded as a program). It is either fully implemented or not implemented at all
4. Some specific operations of the file system are no longer transparent and need the assistance of the application program. The collaborative design of the application program and the file system API improves the flexibility of the whole system. For example, the requirement of GFS consistency model is relaxed, so that the design of file system is greatly simplified without increasing the burden of application. Atomic appending operation is also introced, so that when multiple clients are appending at the same time, there is no need for additional synchronization operation
in short, GFS is designed for the Google App itself. It is said that Google has deployed many GFS clusters. Some clusters have more than 1000 storage nodes and more than 300t of hard disk space, which are frequently accessed by hundreds of clients on different machines.
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