GPGPU

A variety of computational accelerators have been greatly improved in recent years. Intel's MIC (Many Integrated Core) and both GPU architectures, NVIDIA's Kepler and AMD's Graphics Core Next, all represent real innovations in the field of HPC. Based ...

Discrete GPUs in modern multi-GPU systems can transparently access each other's memories through the PCIe interconnect. Future systems will improve this capability by including better GPU interconnects such as NVLink. However, remote memory access ...

Modern graphics processing units (GPUs) include hardware- controlled caches to reduce bandwidth requirements and energy consumption. However, current GPU cache hierarchies are inefficient for general purpose GPU (GPGPU) comput- ing. GPGPU workloads ...

Recent GPUs are equipped with general-purpose L1 and L2 caches in an attempt to reduce memory bandwidth demand and improve the performance of some irregular GPGPU applications. However, due to the massive multithreading, GPGPU caches suffer from severe ...

This paper studies the effects of source-code optimizations on the performance, power draw, and energy consumption of a modern compute GPU. We evaluate 128 versions of two n-body codes: a compute-bound regular implementation and a memory-bound ...

As modern hardware keeps evolving, an increasingly effective approach to develop energy efficient and high-performance solvers is to design them to work on many small size independent problems. Many applications already need this functionality, ...

State of the art automatic optimization of OpenCL applications focuses on improving the performance of individual compute kernels. Programmers address opportunities for inter-kernel optimization in specific applications by ad-hoc hand tuning: manually ...

Irregular algorithms such as Stochastic Gradient Descent (SGD) can benefit from the massive parallelism available on GPUs. However, unlike in data-parallel algorithms, synchronization patterns in SGD are quite complex. Furthermore, scheduling for scale-...

Cellulose is one of the most promising energy resources that is waiting to be tapped. Harvesting energy from cellulose requires decoding its atomic structure. Some structural information can be exposed by modeling data produced by X-ray scattering. ...

Random-restart hill climbing is a common approach to combinatorial optimization problems such as the traveling salesman problem (TSP). We present and evaluate an implementation of random-restart hill climbing with 2-opt local search applied to TSP. Our ...

As architectures evolve, optimization techniques to obtain good performance evolve as well. Using low-level programming languages like C/C++ typically results in architecture-specific optimization techniques getting entangled with the application ...