Reservoir Labs, Inc.

Allen K Leung

Richard A Lethin

Benoit J Meister

David E Wohlford

Nicolas T Vasilache

Peter Szilagyi

Cedric Bastoul

Methods, apparatus and computer software product for optimization of data transfer between two memories includes determining access to master data stored in one memory and/or to local data stored in another memory such that either or both of the size of total data transferred and the number of data transfers required to transfer the total data can be minimized. The master and/or local accesses are based on, at least in part, respective structures of the master and local data.

Methods and apparatus for data transfer optimization

Methods, apparatus and computer software product for source code optimization are provided. In an exemplary embodiment, a first custom computing apparatus is used to optimize the execution of source code on a second computing apparatus. In this embodiment, the first custom computing apparatus contains a memory, a storage medium and at least one processor with at least one multi-stage execution unit. The second computing apparatus contains at least two multi-stage execution units that allow for parallel execution of tasks. The first custom computing apparatus optimizes the code for parallelism, locality of operations and contiguity of memory accesses on the second computing apparatus. This Abstract is provided for the sole purpose of complying with the Abstract requirement rules. This Abstract is submitted with the explicit understanding that it will not be used to interpret or to limit the scope or the meaning of the claims.

System, methods and apparatus for program optimization for multi-threaded processor architectures

Methods, apparatus and computer software product for local memory compaction are provided. In an exemplary embodiment, a processor in connection with a memory compaction module identifies inefficiencies in array references contained within in received source code, allocates a local array and maps the data from the inefficient array reference to the local array in a manner which improves the memory size requirements for storing and accessing the data. In another embodiment, a computer software product implementing a local memory compaction module is provided. In a further embodiment a computing apparatus is provided. The computing apparatus is configured to improve the efficiency of data storage in array references. This Abstract is provided for the sole purpose of complying with the Abstract requirement rules. This Abstract is submitted with the explicit understanding that it will not be used to interpret or to limit the scope or the meaning of the claims.

Methods and apparatus for local memory compaction

Computer-executed transformation of source code enables optimization of the code for one or more of parallelism, locality, and memory footprint of operations represented in the source code on a computing apparatus. This Abstract is provided for the sole purpose of complying with the Abstract requirement rules that allow a reader to quickly ascertain the subject matter of the disclosure contained herein. This Abstract is submitted with the explicit understanding that it will not be used to interpret or to limit the scope or the meaning of the claims.

Methods and apparatus for aggressive scheduling in source code compilation

Methods, apparatus and computer software product for source code optimization are provided. In an exemplary embodiment, a first custom computing apparatus is used to optimize the execution of source code on a second computing apparatus. In this embodiment, the first custom computing apparatus contains a memory, a storage medium and at least one processor with at least one multi-stage execution unit. The second computing apparatus contains at least two multi-stage execution units that avow for parallel execution of tasks. The first custom computing apparatus optimizes the code for both parallelism and locality of operations on the second computing apparatus. This Abstract is provided for the sole purpose of complying with the Abstract requirement rules. This Abstract is submitted with the explicit understanding that it will not be used to interpret or to limit the scope or the meaning of the claims.

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New York, NY, United States of America

Allen K Leung