Impact of data padding on CRC calculation

By -

I am calculating CRC on a large chunk of data every cycle in hardware (64B per cycle). In order to parallelize the CRC calculation, I want to calculate the CRC for small data chunks and then XOR them in parallel.

Approach:

  1. We divide the data into small chunks (64B data divided into 8 chunks of 8B each).
  2. Then we calculate CRC's for all the chunks individually (8 CRC's in parallel for 8B chunks).
  3. Finally calculate the CRC for padded data. This answer points out that the CRC for padded data is obtained by multiplying the old CRC with x^n.

Hence, I am calculating the CRC for a small chunk of data, then multiply it with CRC of 0x1 shifted by 'i' times as shown below.

In short, I am trying to accomplish below: enter image description here

For example: CRC-8 on this site:

Input Data=(0x05 0x07) CRC=0x54
Step-1: Data=0x5 CRC=0x1B
Step-2: Data=0x7 CRC=0x15
Step-3: Data=(0x1 0x0) CRC=0x15
Step-4: Multiply step-1 CRC and step-3 CRC with primitive polynomial 0x7. So, I calculate (0x1B).(0x15) = (0x1 0xC7) mod 0x7.
Step-5: Calculate CRC Data=(0x1 0xC7) CRC=0x4E (I assume this is same as (0x1 0xC7) mod 0x7)
Step-6: XOR the result to get the final CRC. 0x4E^0x15=0x5B

As we can see, the result in step-6 is not the correct result.

Can someone help me how to calculate the CRC for padded data? Or where am I going wrong in the above example?



from Recent Questions - Stack Overflow https://ift.tt/3A5mvtT
https://ift.tt/3qwj7VP

Comments

Post a Comment

Popular posts from this blog

Today Walkin 14th-Sept

By -
Image
14th Sept 2017 ( GO Through all List) Read Walkin details properly , Try to call company before attending if possible !!! ==================================== 1. Myntra through fresherworld (Call Based , Venue shared to shortlisted candidates) _____________________________ 2. Magna : Hiring for Client Harman : C++
Read more

Spring Elasticsearch Operations

By -
Elasticsearch Operations Spring Data Elasticsearch uses two interfaces to define the operations that can be called against an Elasticsearch index. These are ElasticsearchOperations and ReactiveElasticsearchOperations. Whereas the first is used with the classic synchronous implementations, the second one uses reactive infrastructure. The default implementations of the interfaces offer: Read/Write mapping support for domain types. A rich query and criteria api. Resource management and Exception translation. ElasticsearchTemplate The ElasticsearchTemplate is an implementation of the ElasticsearchOperations interface using the Transport Client. @Configuration public class TransportClientConfig extends ElasticsearchConfigurationSupport {   @Bean   public Client elasticsearchClient() throws UnknownHostException {                      Settings settings = Settings.builder().put("cluster.name", "elasticsearch")....
Read more

Hibernate Search - Elasticsearch with JSON manipulation

By -
Elasticsearch with JSON manipulation Elasticsearch ships with many features. It is possible that at some point, one feature you need will not be exposed by the Search DSL. To work around such limitations, Hibernate Search provides ways to: Transform the HTTP request sent to Elasticsearch for search queries. Read the raw JSON of the HTTP response received from Elasticsearch for search queries. Direct changes to the HTTP request may conflict with Hibernate Search features and be supported differently by different versions of Elasticsearch. Similarly, the content of the HTTP response may change depending on the version of Elasticsearch, depending on which Hibernate Search features are used, and even depending on how Hibernate Search features are implemented. Thus, features relying on direct access to HTTP requests or responses cannot be guaranteed to continue to work when upgrading Hibernate Search, even for micro upgrades (x.y.z to x.y.(z+1)). Use this at your own risk....
Read more