Abstract: A method, computer readable medium, and system are disclosed for audio captioning. A raw audio waveform including a non-speech sound is received and relevant features are extracted from the raw audio waveform using a recurrent neural network (RNN) acoustic model. A discrete sequence of characters represented in a natural language is generated based on the relevant features, where the discrete sequence of characters comprises a caption that describes the non-speech sound.

Abstract: A method, system, and computer program product for executing divergent threads using a convergence barrier are disclosed. A first instruction in a program is executed by a plurality of threads, where the first instruction, when executed by a particular thread, indicates to a scheduler unit that the thread participates in a convergence barrier. A first path through the program is executed by a first divergent portion of the participating threads and a second path through the program is executed by a second divergent portion of the participating threads. The first divergent portion of the participating threads executes a second instruction in the program and transitions to a blocked state at the convergence barrier. The scheduler unit determines that all of the participating threads are synchronized at the convergence barrier and the convergence barrier is cleared.

Abstract: A method, computer readable medium, and system are disclosed for audio captioning. A raw audio waveform including a non-speech sound is received and relevant features are extracted from the raw audio waveform using a recurrent neural network (RNN) acoustic model. A discrete sequence of characters represented in a natural language is generated based on the relevant features, where the discrete sequence of characters comprises a caption that describes the non-speech sound.

Abstract: A system, method, and computer program product for ensuring forward progress of threads that implement divergent operations in a single-instruction, multiple data (SIMD) architecture is disclosed. The method includes the steps of allocating a queue data structure to a thread block including a plurality of threads, determining that a current instruction specifies a yield operation, pushing a token onto the second side of the queue data structure, disabling any active threads in the thread block, popping a next pending token from the first side of the queue data structure, and activating one or more threads in the thread block according to a mask included in the next pending token.

Abstract: A method, system, and computer program product for executing divergent threads using a convergence barrier are disclosed. A first instruction in a program is executed by a plurality of threads, where the first instruction, when executed by a particular thread, indicates to a scheduler unit that the thread participates in a convergence barrier. A first path through the program is executed by a first divergent portion of the participating threads and a second path through the program is executed by a second divergent portion of the participating threads. The first divergent portion of the participating threads executes a second instruction in the program and transitions to a blocked state at the convergence barrier. The scheduler unit determines that all of the participating threads are synchronized at the convergence barrier and the convergence barrier is cleared.

Abstract: A system, method, and computer program product are provided for. The method includes the steps of executing a block of translated binary instructions by multiple threads and gathering profiling data during execution of the block of translated binary instructions. The multiple threads are then synchronized at a barrier instruction associated with the block of translated binary instructions and the block of translated binary instructions is replaced with optimized binary instructions, where the optimized binary instructions are produced based on the profiling data.

Abstract: A system, method, and computer program product are provided for. The method includes the steps of executing a block of translated binary instructions by multiple threads and gathering profiling data during execution of the block of translated binary instructions. The multiple threads are then synchronized at a barrier instruction associated with the block of translated binary instructions and the block of translated binary instructions is replaced with optimized binary instructions, where the optimized binary instructions are produced based on the profiling data.

Abstract: A system, method, and computer program product for ensuring forward progress of threads that implement divergent operations in a single-instruction, multiple data (SIMD) architecture is disclosed. The method includes the steps of allocating a queue data structure to a thread block including a plurality of threads, determining that a current instruction specifies a yield operation, pushing a token onto the second side of the queue data structure, disabling any active threads in the thread block, popping a next pending token from the first side of the queue data structure, and activating one or more threads in the thread block according to a mask included in the next pending token.