Design and Development of Stream Processor Architecture for GPU Application Using Reconfigurable Computing

2013 ◽  
Vol 2 (1) ◽  
pp. 1
Author(s):  
Sanket Dessai ◽  
Krishna Bhushan Vutukuru
Keyword(s):  
Reconfigurable Computing ◽  
General Purpose ◽  
Instruction Level Parallelism ◽  
Stream Processor ◽  
Subword Parallelism ◽  
Host Processor ◽  
Graphical Processing ◽  
Processor Unit ◽  
Pipelined Multiplier ◽  
Level Parallelism

Graphical Processing Units (GPUs) have become an integral part of today’s mainstream computing systems. They are also being used as reprogrammable General Purpose GPUs (GP-GPUs) to perform complex scientific computations. Reconfigurability is an attractive approach to embedded systems allowing hardware level modification. Hence, there is a high demand for GPU designs based on reconfigurable hardware. Stream processor consists of clusters of functional units which provide a bandwidth hierarchy, supporting hundreds of arithmetic units. The arithmetic cluster units are designed to exploit instruction level parallelism and subword parallelism within a cluster and data parallelism across the clusters.For decreasing the area and power, a single controller is used to control data flow between clusters and between host processor and GPU. The designed of stream processor unit has been carried out in Verilog on Altera Quartus II and simulated using ModelSim tools. The functionality of the modelled blocks is verified using test inputs in the simulator.The simulated execution time of 8-bit pipelined multiplier is 60 ps and 100 ns for 8-bit pipelined adder while operating at 90 MHz.

scholarly journals FuMicro: A Fused Microarchitecture Design Integrating In-Order Superscalar and VLIW

VLSI Design ◽  
2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Yumin Hou ◽  
Hu He ◽  
Xu Yang ◽  
Deyuan Guo ◽  
Xu Wang ◽  
...  
Keyword(s):  
Digital Signal ◽  
General Purpose ◽  
Instruction Level Parallelism ◽  
Instruction Set ◽  
Mode Switch ◽  
Development Environment ◽  
General Purpose Processor ◽  
Improve Instruction ◽  
Library Function ◽  
Level Parallelism

This paper proposes FuMicro, a fused microarchitecture integrating both in-order superscalar and Very Long Instruction Word (VLIW) in a single core. A processor with FuMicro microarchitecture can work under alternative in-order superscalar and VLIW mode, using the same pipeline and the same Instruction Set Architecture (ISA). Small modification to the compiler is made to expand the register file in VLIW mode. The decision of mode switch is made by software, and this does not need extra hardware. VLIW code can be exploited in the form of library function and the users will be exposed under only superscalar mode; by this means, we can provide the users with a convenient development environment. FuMicro could serve as a universal microarchitecture for it can be applied to different ISAs. In this paper, we focus on the implementation of FuMicro with ARM ISA. This architecture is evaluated on gem5, which is a cycle accurate microarchitecture simulation platform. By adopting FuMicro microarchitecture, the performance can be improved on an average of 10%, with the best performance improvement being 47.3%, compared with that under pure in-order superscalar mode. The result shows that FuMicro microarchitecture can improve Instruction Level Parallelism (ILP) significantly, making it promising to expand digital signal processing capability on a General Purpose Processor.

scholarly journals Boosting Parallel Applications Performance on Applying DIM Technique in a Multiprocessing Environment

2011 ◽  
Vol 2011 ◽  
pp. 1-13 ◽  
Author(s):  
Mateus B. Rutzig ◽  
Antonio C. S. Beck ◽  
Felipe Madruga ◽  
Marco A. Alves ◽  
Henrique C. Freitas ◽  
...  
Keyword(s):  
General Purpose ◽  
Parallel Applications ◽  
Instruction Level Parallelism ◽  
Great Level ◽  
Embedded Processor ◽  
Wide Range ◽  
Thread Level Parallelism ◽  
Multiprocessing Systems ◽  
Performance Gains ◽  
Level Parallelism

Limits of instruction-level parallelism and higher transistor density sustain the increasing need for multiprocessor systems: they are rapidly taking over both general-purpose and embedded processor domains. Current multiprocessing systems are composed either of many homogeneous and simple cores or of complex superscalar, simultaneous multithread processing elements. As parallel applications are becoming increasingly present in embedded and general-purpose domains and multiprocessing systems must handle a wide range of different application classes, there is no consensus over which are the best hardware solutions to better exploit instruction-level parallelism (TLP) and thread-level parallelism (TLP) together. Therefore, in this work, we have expanded the DIM (dynamic instruction merging) technique to be used in a multiprocessing scenario, proving the need for an adaptable ILP exploitation even in TLP architectures. We have successfully coupled a dynamic reconfigurable system to an SPARC-based multiprocessor and obtained performance gains of up to 40%, even for applications that show a great level of parallelism at thread level.

Improving ILP via Fused In-Order Superscalar and VLIW Instruction Dispatch Methods

2018 ◽  
Vol 28 (02) ◽  
pp. 1950020 ◽  
Author(s):  
Yumin Hou ◽  
Xu Wang ◽  
Jiawei Fu ◽  
Junping Ma ◽  
Hu He ◽  
...  
Keyword(s):  
Prediction Method ◽  
Digital Signal ◽  
General Purpose ◽  
Performance Comparison ◽  
Instruction Level Parallelism ◽  
Superscalar Processor ◽  
Performance Improvements ◽  
General Purpose Processor ◽  
Evaluation Board ◽  
Level Parallelism

In order to expand the computation capability of digital signal processing on a General Purpose Processor (GPP), we propose a fused microarchitecture that improves Instruction Level Parallelism (ILP) by supporting both in-order superscalar and very long instruction word (VLIW) dispatch methods in a single pipeline. This design is based on ARMv7-A&R Instruction Set Architecture (ISA). To provide a performance comparison, we first design an in-order superscalar processor, considering that ARM GPPs always adopt superscalar approaches. And then we expand VLIW dispatch method based on this processor, to realize the fused microarchitecture. The two designs are both evaluated on the Xilinx 7-series FPGA (XC7K325T-2FFG900C), using Xilinx Vivado design suite. The results show that, compared with the superscalar processor, the processor working under VLIW mode can improve the performance by 15% and 8%, respectively, when running EEMBC and DSPstone benchmarks. We also run the two benchmarks on ARM Cortex-A9 processor, which is integrated in the Zynq-7000 AP SoC device on Xilinx ZC706 evaluation board. The processor in VLIW mode shows 44% and 30% performance improvements than ARM Cortex-A9. The fused microarchitecture adopts a combined bimodal and PAp branch prediction method. This method achieves 93.7% prediction accuracy with limited hardware overhead.

Design and Development of Texture Filtering Architecture for GPU Application Using Reconfigurable Computing

2012 ◽  
Vol 1 (3) ◽  
pp. 108
Author(s):  
Sanket Suresh Naik Dessai
Keyword(s):  
Reconfigurable Computing ◽  
General Purpose ◽  
Reconfigurable Hardware ◽  
High Demand ◽  
Computing Systems ◽  
Graphical Processing Units ◽  
Quartus Ii ◽  
Filter Unit ◽  
Texture Filtering ◽  
Graphical Processing

Graphical Processing Units (GPUs) have become an integral part of today’s mainstream computing systems. They are also being used as reprogrammable General Purpose GPUs (GP-GPUs) to perform complex scientific computations. Reconfigurability is an attractive approach to embedded systems allowing hardware level modification.  Hence, there is a high demand for GPU designs based on reconfigurable hardware. The texture filter unit is designed to process geometric data like vertices and convert these into pixels on the screen. This process involves number of operations, like circle and cube generation, rotator, and scaling. The texture filter unit is designed with all necessary hardware to deal with all the different filtering operations. The designed texture filtering units are modelled in Verilog on Altera Quartus II and simulated using ModelSim tools. The functionality of the modelled blocks is verified using test inputs in the simulator.Circle and cube coordinates are generated for circle and cube generation. The work can form the basis for designing a complete reconfigurable GPU.

Optimizing Techniques for OpenCL Programs on Heterogeneous Platforms

2012 ◽  
Vol 4 (3) ◽  
pp. 48-62
Author(s):  
Slo-Li Chu ◽  
Chih-Chieh Hsiao
Keyword(s):  
General Purpose ◽  
Optimization Techniques ◽  
Instruction Level Parallelism ◽  
Heterogeneous Platforms ◽  
Modern Computer ◽  
Level Data ◽  
Performance Programming ◽  
Architectural Characteristics ◽  
Level Parallelism

Heterogeneous platforms that are consisted of CPU and add-on streaming processors are widely used in modern computer systems. These add-on processors provide substantially more computation capability and memory bandwidth than conventional multi-cores platforms. General-purpose computations can also be leveraged onto these add-on processors. In order to utilize their potential performance, programming these streaming processors is challenging because of their diverse underlying architectural characteristics. Several optimization techniques are applied on OpenCL-compatible heterogeneous platforms to achieve thread-level, data-level, and instruction-level parallelism. The architectural implications of these techniques and optimization principles are discussed. Finally, a case study of MRI-Q benchmark will be addressed to illustrate to capabilities of these optimization techniques. The experimental results reveal the speedup from non-optimized to optimized kernel can vary from 8 to 63 on different target platforms.

scholarly journals Microarchitectural Characterization on a Mobile Workload

2021 ◽  
Vol 11 (3) ◽  
pp. 1225
Author(s):  
Woohyong Lee ◽  
Jiyoung Lee ◽  
Bo Kyung Park ◽  
R. Young Chul Kim
Keyword(s):  
Performance Monitoring ◽  
Performance Metrics ◽  
Performance Comparison ◽  
Instruction Level Parallelism ◽  
Data Set ◽  
Performance Events ◽  
Hardware Performance Counters ◽  
On Chip ◽  
The Comparative Study ◽  
Level Parallelism

Geekbench is one of the most referenced cross-platform benchmarks in the mobile world. Most of its workloads are synthetic but some of them aim to simulate real-world behavior. In the mobile world, its microarchitectural behavior has been reported rarely since the hardware profiling features are limited to the public. As a popular mobile performance workload, it is hard to find Geekbench’s microarchitecture characteristics in mobile devices. In this paper, a thorough experimental study of Geekbench performance characterization is reported with detailed performance metrics. This study also identifies mobile system on chip (SoC) microarchitecture impacts, such as the cache subsystem, instruction-level parallelism, and branch performance. After the study, we could understand the bottleneck of workloads, especially in the cache sub-system. This means that the change of data set size directly impacts performance score significantly in some systems and will ruin the fairness of the CPU benchmark. In the experiment, Samsung’s Exynos9820-based platform was used as the tested device with Android Native Development Kit (NDK) built binaries. The Exynos9820 is a superscalar processor capable of dual issuing some instructions. To help performance analysis, we enable the capability to collect performance events with performance monitoring unit (PMU) registers. The PMU is a set of hardware performance counters which are built into microprocessors to store the counts of hardware-related activities. Throughout the experiment, functional and microarchitectural performance profiles were fully studied. This paper describes the details of the mobile performance studies above. In our experiment, the ARM DS5 tool was used for collecting runtime PMU profiles including OS-level performance data. After the comparative study is completed, users will understand more about the mobile architecture behavior, and this will help to evaluate which benchmark is preferable for fair performance comparison.

scholarly journals UltraSynth: Insights of a CGRA Integration into a Control Engineering Environment

2021 ◽  
Author(s):  
Dennis Wolf ◽  
Andreas Engel ◽  
Tajas Ruschke ◽  
Andreas Koch ◽  
Christian Hochberger
Keyword(s):  
Computing System ◽  
Coarse Grained ◽  
Instruction Level Parallelism ◽  
Control Engineering ◽  
Processing Elements ◽  
Actual Application ◽  
Reconfigurable Arrays ◽  
Engineering Environment ◽  
On Chip ◽  
Level Parallelism

AbstractCoarse Grained Reconfigurable Arrays (CGRAs) or Architectures are a concept for hardware accelerators based on the idea of distributing workload over Processing Elements. These processors exploit instruction level parallelism, while being energy efficient due to their simplistic internal structure. However, the incorporation into a complete computing system raises severe challenges at the hardware and software level. This article evaluates a CGRA integrated into a control engineering environment targeting a Xilinx Zynq System on Chip (SoC) in detail. Besides the actual application execution performance, the practicability of the configuration toolchain is validated. Challenges of the real-world integration are discussed and practical insights are highlighted.

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