GPU Architecture

本團隊目前的研究主題如下：

隨著GPU技術的進步與繪圖效能的提升，視覺運算領域正快速的發展。使用GPU來做大量平行處理的通用運算GPU(GPGPU - General Purpose GPU)，以及整合CPU與GPU的異質性系統，不但大幅提升了運算效能，更是研究的趨勢之一。HSA Foundation所提出的Heterogeneous System Architecture，便希望整合CPU與GPU的架構，進一步提升整個系統運算的效能。
Fig. 1: HSA

1. HSA Immediate Language
   HSA introduced a low-level intermediate language, which is portable across multiple platforms.
2. Hetergeneous Uniform Memory Access (hUMA)
   Unified Memory Address Space reduces memory bandwidth between CPU and GPU to improve performance.
3. Hetergeneous Queuing (hQ)
   GPU and CPU have equal flexibility to create and dispatch work items which reduces dispatch latency to GPU.

Fig. 2: GPU Simulator 為了研究並且模擬異質系統架構的運算，我們實作了一個基於異質系統架構(HSA)的GPU模擬器。此模擬器包含：

1. Custom GPU ISA
   Which is based on the HSAIL BRIG and Nvidia PTX Virtual ISA
2. HSAIL to HSA Binary Translator
3. GPU Simulator

A fundamental GPU Simulator based on our Custom GPU ISA which includes fixed-size register file, warp scheduler, dispatch unit and SIMD execution units for parallel computing. The Simulator also supports 80 of 110 (73%) instructions, and solution to the divergent control flow and synchronization.

1. HSA Foundation