Sparsh Mittal
Initially introduced as special-purpose accelerators for graphics applications, graphics processing units (GPUs) have now emerged as general purpose computing platforms for a wide range of applications. To address the requirements of these applications, modern GPUs include sizable hardware-managed caches. However, several factors, such as unique architecture of GPU, rise of CPU–GPU heterogeneous computing, etc., demand […]
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Rita Borgo, Ken Brodlie
This report aims to provide a beginner’s introduction to GPUs, from both a hardware and a software angle. We look at the evolution of specialist graphics hardware from the early days of PC graphics cards to the present day. We describe the currently available hardware from NVIDIA and AMD/ATI, and the current software from both […]
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Yifang Liu, Jiang Hu
The progress of GPU (Graphics Processing Unit) technology opens a new avenue for boosting computing power. This work is an attempt to exploit GPU for accelerating VLSI circuit optimization. We propose GPU-based parallel computing techniques and apply them on simultaneous gate sizing and threshold voltage assignment, which is often employed in practice for performance and […]
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William Mark
Graphics architectures are in the midst of a major transition. In the past, these were specialized architectures designed to support a single rendering algorithm: the standard Z buffer. Realtime 3D graphics has now advanced to the point where the Z-buffer algorithm has serious shortcomings for generating the next generation of higher-quality visual effects demanded by […]
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Larry Seiler, Doug Carmean, Eric Sprangle, Tom Forsyth, Michael Abrash, Pradeep Dubey, Stephen Junkins, Adam Lake, Jeremy Sugerman, Robert Cavin, Roger Espasa, Ed Grochowski, Toni Juan, Pat Hanrahan
This paper presents a many-core visual computing architecture code named Larrabee, a new software rendering pipeline, a manycore programming model, and performance analysis for several applications. Larrabee uses multiple in-order x86 CPU cores that are augmented by a wide vector processor unit, as well as some fixed function logic blocks. This provides dramatically higher performance […]
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Henry Wong, Anne Bracy, Ethan Schuchman, Tor M. Aamodt, Jamison D. Collins, Perry H. Wang, Gautham Chinya, Ankur K. Groen, Hong Jiang, Hong Wang
Moore’s Law and the drive towards performance efficiency have led to the on-chip integration of general-purpose cores with special-purpose accelerators. Pangaea is a heterogeneous CMP design for non-rendering workloads that integrates IA32 CPU cores with non-IA32 GPU-class multi-cores, extending the current state-of-the-art CPU-GPU integration that physically “fuses” existing CPU and GPU designs. Pangaea introduces (1) […]
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John Owens
Abstract not available
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Wilson W. L. Fung, Ivan Sham, George Yuan, Tor M. Aamodt
Recent advances in graphics processing units (GPUs) have resulted in massively parallel hardware that is easily programmable and widely available in commodity desktop computer systems. GPUs typically use single-instruction, multiple-data (SIMD) pipelines to achieve high performance with minimal overhead incurred by control hardware. Scalar threads are grouped together into SIMD batches, sometimes referred to as […]
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Jeremy W. Sheaffer, David P. Luebke, Kevin Skadron
With shrinking process technology, the primary cause of transient faults in semiconductors shifts away from high-energy cosmic particle strikes and toward more mundane and pervasive causes—power fluctuations, crosstalk, and other random noise. Smaller transistor features require a lower critical charge to hold and change bits, which leads to faster microprocessors, but which also leads to […]
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Emmett Kilgariff, Randima Fernando
The previous chapter described how GPU architecture has changed as a result of computational and communications trends in microprocessing. This chapter describes the architecture of the GeForce 6 Series GPUs from NVIDIA, which owe their formidable computational power to their ability to take advantage of these trends. Most notably, we focus on the GeForce 6800 […]
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Martin Dimitrov, Mike Mantor, Huiyang Zhou
Even though graphics processors (GPUs) are becoming increasingly popular for general purpose computing, current (and likely near future) generations of GPUs do not provide hardware support for detecting soft/hard errors in computation logic or memory storage cells since graphics applications are inherently fault tolerant. As a result, if an error occurs in GPUs during program […]
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Kyusik Chung, Chang-Hyo Yu, Donghyun Kim, Lee-Sup Kim
In this paper, we propose an architecture of tessellation hardware to save memory bandwidth in a mobile multimedia processor. To reduce the implementation overhead, floating-point computations of tessellation are accelerated by the conventional GPU pipeline, and only tessellation-specific control logic is handled by an additional hardware unit. Tightly coupled with a vertex shader, the additional […]
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