LogCA: A Performance Model for Hardware Accelerators
LogCA: A Performance Model for Hardware Accelerators
复制标题
LogCA：硬件加速器的性能模型
DOI：
10.1109/lca.2014.2360182
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发表时间：
2015
影响因子：
2.3
通讯作者：
D. Wood
中科院分区：
文献类型：
--
作者：
Muhammad Shoaib Bin Altaf;D. Wood
为了解决暗硅问题，架构师越来越多地转向专用硬件加速器，以提高加密和压缩等通用计算内核的性能和能效。不幸的是，将计算卸载到加速器所需的延迟和开销有时超过了潜在的好处，导致性能或能源效率的净下降。为了帮助架构师和程序员考虑这些权衡，我们开发了 LogCA 模型，这是一个简单的硬件加速器性能模型。 LogCA 提供了硬件加速器的简化抽象，具有五个关键参数。我们针对各种加速器验证了该模型，从 Sun 的 UltraSparc T2 和英特尔的 Sandy Bridge 中的片上加密加速器到离散和集成 GPU。
To address the Dark Silicon problem, architects have increasingly turned to special-purpose hardware accelerators to improve the performance and energy efficiency of common computational kernels, such as encryption and compression. Unfortunately, the latency and overhead required to off-load a computation to an accelerator sometimes outweighs the potential benefits, resulting in a net decrease in performance or energy efficiency. To help architects and programmers reason about these trade-offs, we have developed the LogCA model, a simple performance model for hardware accelerators. LogCA provides a simplified abstraction of a hardware accelerator characterized by five key parameters. We have validated the model against a variety of accelerators, ranging from on-chip cryptographic accelerators in Sun's UltraSparc T2 and Intel's Sandy Bridge to both discrete and integrated GPUs.