A portable platform for accelerated PIC codes and its application to GPUs using OpenACC

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The demise of Moore's Law and Dennard scaling has resulted in diminishing performance gains for general-purpose processors, and so has prompted a surge in academic and commercial interest for hardware accelerators. Specialized hardware has already redefine ...

Compute memories are memory arrays augmented with dedicated logic to support arithmetic. They support the efficient execution of data-centric computing patterns, such as those characterizing Artificial Intelligence (AI) algorithms. These architectures can ...

Developing and fine-tuning software programs for heterogeneous hardware such as CPU/GPU processing platforms comprise a highly complex endeavor that demands considerable time and effort of software engineers and requires evaluating various fundamental comp ...

Timely insights lead to business growth and scientific breakthroughs but require analytical engines that cope with the ever-increasing data processing needs. Analytical engines relied on rapid CPU improvements, yet the end of Dennard scaling stopped the fr ...

Writing and optimizing application software for heterogeneous platforms including GPU units is a very difficult task that requires designer efforts and resources to consider several key elements to obtain good performance. Dataflow programming has shown to ...

Recent GPU architectures make available numbers of parallel processing units that exceed by orders of magnitude the ones offered by CPU architectures. Whereas programs written using dataflow programming languages are well suited for programming heterogeneo ...

The performance of programs executed on heterogeneous parallel platforms largely depends on the design choices regarding how to partition the processing on the various different processing units. In other words, it depends on the assumptions and parameters ...

Computing servers play a key role in the development and process of emerging compute-intensive applications in recent years. However, they need to operate efficiently from an energy perspective viewpoint, while maximizing the performance and lifetime of th ...

The conjugate heat transfer in mixtures of a fluid and single granular clusters is studied in this paper using a novel lattice Boltzmann method (LBM) programmed for parallel computation on the graphics processing unit (GPU). The LBM is validated for heat c ...

Field-programmable gate arrays (FPGAs) combine hardware reconfigurability with a high degree of parallelism. Consequently, FPGAs offer performance gains and power savings for many applications. A recent trend has been to leverage the hardware versatility o ...

Edge-computing requires high-performance energy-efficient embedded systems. Fixed-function or custom accelerators, such as FFT or FIR filter engines, are very efficient at implementing a particular functionality for a given set of constraints. However, the ...

In order to develop sustainable and more powerful information technology (IT) infrastructures, the challenges posed by the "memory wall" are critical for the design of high-performance and high-efficiency many-core computing systems. In this context, recen ...

A portable platform for accelerated PIC codes and its application to GPUs using OpenACC

Chattez avec Graph Search

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Dynamic SIMD Parallel Execution on GPU from High-Level Dataflow Synthesis

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SIMD Parallel Execution on GPU from High-Level Dataflow Synthesis

Inter-actions parallel execution on GPU from high-level dataflow synthesis

Performance Estimation of High-Level Dataflow Program on Heterogeneous Platforms by Dynamic Network Execution

Reinforcement Learning-Based Joint Reliability and Performance Optimization for Hybrid-Cache Computing Servers

Conjugate heat transfer in isolated granular clusters with interstitial fluid using lattice Boltzmann method

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Full System Exploration of On-Chip Wireless Communication on Many-Core Architectures