Cited by 64

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A fully integrated multi-CPU, GPU and memory controller 32nm processor

Yuffe, Marcelo, Knoll, Ernest, Mehalel, Moty, Shor, Joseph, Kurts, Tsvika·2011·2011 IEEE International Solid-State Circuits Conference

Abstract

This paper describes the 32nm Sandy Bridge processor that integrates up to 4 high performance Intel Architecture (IA) cores, a power/performance optimized graphic processing unit (GPU) and memory and PCIe controllers in the same die. The Sandy Bridge architecture block diagram is shown in Fig. 15.1.1 and the floorplan of a four IA-core version is shown in Fig. 15.1.2. The Sandy Bridge IA core implements an improved branch prediction algorithm, a micro-operation (Uop) cache, a floating point Advanced Vector Extension (AVX), a second load port in the L1 cache and bigger register files in the out-of-order part of the machine; all these architecture improvements boost the IA core performance without increasing the thermal power dissipation envelope or the average power consumption (to preserve battery life in mobile systems). The CPUs and GPU share the same 8MB level-3 cache memory. The data flow is optimized by a high performance on die interconnect fabric (called “ring”) that connects between the CPUs, the GPU, the L3 cache and the system agent (SA) unit that houses a 1600MT/s, dual channel DDR3 memory controller, a 20-lane PCIe gen2 controller, a two parallel pipe display engine, the power management control unit and the testability logic. An on die EPROM is used for configurability and yield optimization.

Overview

Integrity signals

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Crossref · 10.1109/isscc.2011.5746311

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  • Many processors with CPU and GPU on the same chip have already been produced, such as AMD Llano, Intel Sandy Bridge, and Ivy Bridge.

    “An even closer level of integration between CPU and GPU can be achieved by fabricating them on the same chip and many such processors have already been produced, such as AMD Llano [Branover et al. 2012], Intel Sandy Bridge [Yuffe et al. 2011], Ivy Bridge [Damaraju et al. 2012] etc.”

    From A Survey of CPU-GPU Heterogeneous Computing Techniques (2015) · cites this paper as Yuffe et al. 2011

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Research works printed but not linked: 4

  1. 10.1109/ISCAS.2010.5537829 · DOI
  2. 10.1109/CICC.2007.4405718 · DOI
  3. 10.1109/VLSIC.2003.1221150 · DOI
  4. 10.1109/ISSCC.2009.4977305 · DOI

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Metadata

Authors
Yuffe, M., Knoll, E., Mehalel, M., Shor, J., & Kurts, T.
Venue
2011 IEEE International Solid-State Circuits Conference
Publisher
IEEE
Published
2011-02
Pages
264-266
Cited by
64
References
0

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