Scinovex
articleTop 1% cited

Larrabee

ACM Transactions on Graphics · 2008 · Vol. 27(3) · pp. 1–15
Larry SeilerDoug CarmeanEric SprangleTom ForsythMichael AbrashPradeep DubeyStephen JunkinsAdam LakeJeremy SugermanRobert CavinRoger EspasaEd GrochowskiToni JuanPat Hanrahan

Abstract

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 per watt and per unit of area than out-of-order CPUs on highly parallel workloads. It also greatly increases the flexibility and programmability of the architecture as compared to standard GPUs. A coherent on-die 2 nd level cache allows efficient inter-processor communication and high-bandwidth local data access by CPU cores. Task scheduling is performed entirely with software in Larrabee, rather than in fixed function logic. The customizable software graphics rendering pipeline for this architecture uses binning in order to reduce required memory bandwidth, minimize lock contention, and increase opportunities for parallelism relative to standard GPUs. The Larrabee native programming model supports a variety of highly parallel applications that use irregular data structures. Performance analysis on those applications demonstrates Larrabee's potential for a broad range of parallel computation.

Parallel Computing and Optimization TechniquesDistributed and Parallel Computing SystemsAdvanced Neural Network ApplicationsComputer scienceParallel computingx86Rendering (computer graphics)Computer architectureSoftwareMemory bandwidthOperating systemComputer graphics (images)
Citations
780
FWCI
168.61
field-weighted impact
References
55
Percentile
100%
vs. same field & year
Citations per year
References
Brook for GPUs
ACM Transactions on Graphics · 2004 · 1,162 citations
Citation Network

How this paper connects to the literature. Drag to explore, click any node to open that paper.

Larrabee · Scinovex