Semantic Scholar uses AI to extract papers important to this topic.
Language model pre-training has proven to be useful in learning universal language representations. As a state-of-the-art… Expand Most content providers are interested in providing good video delivery QoE for all users, not just on average. State-of-the-art… Expand We present an auto-tuning system for optimizing I/O performance of HDF5 applications and demonstrate its value across platforms… Expand MapReduce, which is the de facto programming model for large-scale distributed data processing, and its most popular… Expand Determining the best set of optimizations to apply to a kernel to be executed on the graphics processing unit (GPU) is a… Expand The rapidly evolving landscape of multicore architectures makes the construction of efficient libraries a daunting task. A family… Expand We present a performance model-driven framework for automated performance tuning (autotuning) of sparse matrix-vector multiply… Expand The development of high performance dense linear algebra (DLA) critically depends on highly optimized BLAS, and especially on the… Expand In this paper, we describe transformation recipes, which provide a high-level interface to the code transformation and code… Expand It is often impossible to obtain a one-size-fits-all solution for high performance algorithms when considering different choices… Expand