Reservoir Labs, Inc.

Qualcomm Incorporated

Significs and Elements, LLC

Nicolas T Vasilache

Richard A Lethin

Benoit J Meister

Muthu Manikandan Baskaran

James Ezick

David E Wohlford

Allen K Leung

Thomas Henretty

Jonathan Springer

M H Langston

Peter Szilagyi

Cedric Bastoul

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 one local memory unit that allows for data reuse opportunities. The first custom computing apparatus optimizes the code for reduced communication execution 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.

Methods and apparatus for automatic communication optimizations in a compiler based on a polyhedral representation

In a system for enabling configuration of an ensemble of several solvers, such that the ensemble can efficiently solve a constraint problem, for each one of several candidate configurations, an array of scores is computed. The array corresponds to a statistical parameter related to a problem solution, and the computation is based on, at least in part, a set of features associated with the problem. One candidate configuration is assigned to a solver, and based on the array of scores associated with that candidate configuration the same or a different candidate configuration is assigned to a another solver. A system for dynamically reconfiguring an ensemble of solvers obtains runtime data from several solvers, and a new configuration is determined by applying a machine learning and/or heuristic analysis procedure to the runtime data. The configuration of a solver may be updated according to the new configuration while that solver is running.

System and method for configuration of an ensemble solver

In a system for automatic generation of event-driven, tuple-space based programs from a sequential specification, a hierarchical mapping solution can target different runtimes relying on event-driven tasks (EDTs). The solution uses loop types to encode short, transitive relations among EDTs that can be evaluated efficiently at runtime. Specifically, permutable loops translate immediately into conservative point-to-point synchronizations of distance one. A runtime-agnostic which can be used to target the transformed code to different runtimes.

System and method for generation of event driven, tuple-space based programs

In a system for storing in memory a tensor that includes at least three modes, elements of the tensor are stored in a mode-based order for improving locality of references when the elements are accessed during an operation on the tensor. To facilitate efficient data reuse in a tensor transform that includes several iterations, on a tensor that includes at least three modes, a system performs a first iteration that includes a first operation on the tensor to obtain a first intermediate result, and the first intermediate result includes a first intermediate-tensor. The first intermediate result is stored in memory, and a second iteration is performed in which a second operation on the first intermediate result accessed from the memory is performed, so as to avoid a third operation, that would be required if the first intermediate result were not accessed from the memory.

Efficient and scalable storage of sparse tensors

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 one local memory unit that allows for data reuse opportunities. The first custom computing apparatus optimizes the code for reduced communication execution on the second computing apparatus.

Efficient and scalable computations with sparse tensors

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 one vector execution unit that allow for parallel execution of tasks on constant-strided memory locations. The first custom computing apparatus optimizes the code for parallelism, locality of operations, constant-strided memory accesses and vectorized execution 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.

Methods and apparatus for joint scheduling and layout optimization to enable multi-level vectorization

A scheduling system can schedule several operations for parallel execution on a number of work processors. At least one of the operations is not to be executed, and the determination of which operation or operations are not to be executed and which ones are to be executed can be made only at run time. The scheduling system partitions a subset operations that excludes the one or more operation that are not to be executed into several groups based on, at least in part, an irregularity of operations resulting from the one or more operation that are not to be executed. In addition, the partitioning is based on, at least in part, locality of data elements associated with the subset of operations to be executed or loading of the several work processors.

Systems and methods for parallelizing and optimizing sparse tensor computations

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 making a decision based on the semantics of formal logic are provided. In an exemplary embodiment, two custom computing apparatuses are used to resolve the satisfiability of a logical formula and provide an example. In this embodiment, the two custom computing apparatuses operate in concert to explore the space of possible satisfying examples. 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.

Systems, methods and apparatus for distributed decision processing

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.

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New York, NY, United States of America

Nicolas T Vasilache