Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Tsung Tai Yeh"'
Publikováno v:
Proceedings of the 28th Asia and South Pacific Design Automation Conference.
Publikováno v:
2022 19th International SoC Design Conference (ISOCC).
Publikováno v:
ACM Transactions on Parallel Computing. 6:1-23
Massively multithreaded GPUs achieve high throughput by running thousands of threads in parallel. To fully utilize the their hardware, contemporary workloads spawn work to the GPU in bulk by launching large tasks, where each task is a kernel that con
Publikováno v:
HPCA
Contemporary GPUs are widely used for throughput-oriented data-parallel workloads and increasingly are being considered for latency-sensitive applications in datacenters. Examples include recurrent neural network (RNN) inference, network packet proce
Publikováno v:
ASPLOS
In massively multithreaded architectures, redundantly executing the same instruction with the same operands in different threads is a significant source of inefficiency. This paper introduces Dimensionality-Aware Redundant SIMT Instruction Eliminatio
Autor:
Tsung-Tai Yeh
Efficient GPU applications rely on programmers carefully structure their codes to fully utilize the GPU resources. In general, programmers spend a significant amount of time optimizing their applications to run efficiently on domain-specific architec
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::06d69f039f3ea65b35e83d43d93b0471
Autor:
Bradford M. Beckmann, Tsung Tai Yeh, Xianwei Zhang, Alexandru Dutu, Anthony Gutierrez, Onur Kayiran, Srikant Bharadwaj, Matthew D. Sinclair, Michael LeBeane, Sooraj Puthoor, Johnathan Alsop, Brandon Potter
Publikováno v:
IISWC
In recent years, machine intelligence (MI) applications have emerged as a major driver for the computing industry. Optimizing these workloads is important, but complicated. As memory demands grow and data movement overheads increasingly limit perform
Publikováno v:
PPOPP
Massively multithreaded GPUs achieve high throughput by running thousands of threads in parallel. To fully utilize the hardware, workloads spawn work to the GPU in bulk by launching large tasks, where each task is a kernel that contains thousands of
Publikováno v:
ACM Transactions on Storage. 11:1-21
Previous studies proposed energy-efficient solutions, such as multispeed disks and disk spin-down methods, to conserve power in their respective storage systems. However, in most cases, the authors did not analyze the reliability of their solutions.
Publikováno v:
PACT
Massively multithreaded GPUs achieve high throughput by running thousands of threads in parallel. To fully utilize the hardware, contemporary workloads spawn work to the GPU in bulk by launching large tasks, where each task is a kernel that contains