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ARTs:

Data Processing
Benefit hypothesis:

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Improves quality and integrity of the PANDA code and at the same time provides a training opportunity for a new member

FTAOD the functionality of this code will not change hence it is a refactoring exercise

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Improves quality and integrity of the PANDA code and at the same time provides a training opportunity for a new member FTAOD the functionality of this code will not change hence it is a refactoring exercise
Acceptance criteria:

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Given - We are developing a CHEETAH module which uses both CPU and GPU accelerator.

When - We need to process the Time-Frequency blocks, which also involves moving the data between GPU and CPU.

Then - The developer will have a single line of code which performs the tasks optimally.

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Given - We are developing a CHEETAH module which uses both CPU and GPU accelerator. When - We need to process the Time-Frequency blocks, which also involves moving the data between GPU and CPU. Then - The developer will have a single line of code which performs the tasks optimally.
Feature Points:
2
Initial Size:
18
WSJF:
5
Epic Link:
PSS Pipeline MVP
Story Point Burn-up:
Overdue:
Outcomes:

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Insert links to relevant docs and / or code here:

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Insert links to relevant docs and / or code here:
Resolved PI.Sprint:
9.6

Refactor existing PSS PANDA pipeline code

Child Of

SS-8 Technical Debt - Feature Set

Story Point Burn-up: (0%)

Feature Estimate: 2.0

Refactor PSS PANDA Pipeline Code for improved stability and interoperability between CPU and GPU accelerators