Difference between revisions of "The NaplesPU Hardware architecture"
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| − | The '''nu+''' manycore is a parametrizable regular mesh Network on Chip (NoC) of configurable tile, developed by CeRICT in the framework of the MANGO FETHPC project. The main objective of | + | The '''nu+''' manycore is a parametrizable regular mesh Network on Chip (NoC) of configurable tile, developed by CeRICT in the framework of the MANGO FETHPC project. The main objective of '''nu+''' is to enable resource-efficient HPC based on special-purpose customized hardware. Our aim is to build an application-driven architecture to achieve the best hardware/software configuration for any data-parallel kernel. Specialized data-parallel accelerators have been known to provide higher efficiency than general-purpose processors for codes with significant amounts of regular data-level parallelism (DLP). However every parallel kernel has its own ideal configuration. |
| − | Each nu+ tile has the same basic components, it provides a | + | Each nu+ tile has the same basic components, it provides a configurable GPU-like open-source soft-core meant to be used as a configurable FPGA overlay. This HPC-oriented accelerator merges the SIMT paradigm with vector processor model. Furthermore, each tile has a Cache Controller and a Directory Controller, those components handle data coherence between different cores in different tiles. |
[[File:Manycore.png|800px|nu+ manycore architecture]] | [[File:Manycore.png|800px|nu+ manycore architecture]] | ||
Revision as of 16:11, 21 November 2018
The nu+ manycore is a parametrizable regular mesh Network on Chip (NoC) of configurable tile, developed by CeRICT in the framework of the MANGO FETHPC project. The main objective of nu+ is to enable resource-efficient HPC based on special-purpose customized hardware. Our aim is to build an application-driven architecture to achieve the best hardware/software configuration for any data-parallel kernel. Specialized data-parallel accelerators have been known to provide higher efficiency than general-purpose processors for codes with significant amounts of regular data-level parallelism (DLP). However every parallel kernel has its own ideal configuration.
Each nu+ tile has the same basic components, it provides a configurable GPU-like open-source soft-core meant to be used as a configurable FPGA overlay. This HPC-oriented accelerator merges the SIMT paradigm with vector processor model. Furthermore, each tile has a Cache Controller and a Directory Controller, those components handle data coherence between different cores in different tiles.
User design can set an high number of parameter for every need, such as:
- NoC topology and Tile number.
- Threads per core number. Each thread has a different PC, so one core can executes as many program as many threads it has.
- Hardware lanes per thread. Each thread can be a vector operation (here called hardware lane).
- Register file size (scalar and vector).
- L1 and L2 cache size and way number.
There are all the hardware main section. Each of them covers important aspects of the hardware.
