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LOCAL foilset Processing-In-Memory (PIM) Architectures for Very High Performance MPP Computing

Given by Peter Kogge Notre Dame at PAWS 96 Mandalay Beach on April 21-26 1996. Foils prepared June 1996
More Detail! * Foil Index from this file *

This was part of a set of PAWS 96(Mandalay Beach) Presentations
Kogge and Collaboraters describe PIM as an emerging architecture where logic and memory combined on same chip which increases memory bandwidth naturally
Conventional Architectures tend to waste transistors measured in terms silicon used per unit operation
Both Existing designs and projections to PetaFlop timescale(2007) are given


Table of Contents for Processing-In-Memory (PIM) Architectures for Very High Performance MPP Computing


1 Separate IMAGE * Separate HTML Processing-In-Memory (PIM) Architectures for Very High Performance MPP Computing
2 Separate IMAGE * Separate HTML Acknowledgements
3 Separate IMAGE * Separate HTML Memory & CPU Bandwidth Gap
4 Separate IMAGE * Separate HTML Key Points
5 Separate IMAGE * Separate HTML This Talk: A Better Way!
6 Separate IMAGE * Separate HTML Observations on This Talk
7 Separate IMAGE * Separate HTML HPCC & TeraFlops
8 Separate IMAGE * Separate HTML Petaflop Chain of Events
9 Separate IMAGE * Separate HTML Results from Pasadena `94
10 Separate IMAGE * Separate HTML PetaFlops Applications
11 Separate IMAGE * Separate HTML Pasadena Architectures
12 Separate IMAGE * Separate HTML Bodega Bay: Primary Memory
13 Separate IMAGE * Separate HTML Bodega Bay: Secondary Memory
14 Separate IMAGE * Separate HTML Bodega Bay: Aggregate I/O
15 Separate IMAGE * Separate HTML Cost Considerations: Processors
16 Separate IMAGE * Separate HTML Cost Considerations: Memory
17 Separate IMAGE * Separate HTML The "Hidden Costs" of Modern Systems
18 Separate IMAGE * Separate HTML The Overlooked Bandwidth
19 Separate IMAGE * Separate HTML Modern "Alternative" RAMs
20 Separate IMAGE * Separate HTML Processing In Memory (PIM): Reclaiming the Bandwidth
21 Separate IMAGE * Separate HTML PIM: Optimizing the System
22 Separate IMAGE * Separate HTML Market Demand for Dense Processing
23 Separate IMAGE * Separate HTML Current PIM Chips
24 Separate IMAGE * Separate HTML Key Problem: Memory Density
25 Separate IMAGE * Separate HTML Vendors with Known DRAM PIM Capability
26 Separate IMAGE * Separate HTML EXECUBE: The First High Density PIM
27 Separate IMAGE * Separate HTML Execube Processing Node
28 Separate IMAGE * Separate HTML Tiling of Execube Processing Nodes
29 Separate IMAGE * Separate HTML Lessons Learned from EXECUBE
30 Separate IMAGE * Separate HTML New "Strawman" PIM Processing Node Macro
31 Separate IMAGE * Separate HTML "Strawman" Chip Floorplan
32 Separate IMAGE * Separate HTML Strawman Chip Interfaces
33 Separate IMAGE * Separate HTML Strawman PIM Chip with I/O Macros
34 Separate IMAGE * Separate HTML Strawman Properties
35 Separate IMAGE * Separate HTML Strawman PIM "Memory Card"
36 Separate IMAGE * Separate HTML Choosing the Processing Macro
37 Separate IMAGE * Separate HTML Performance Per Transistor
38 Separate IMAGE * Separate HTML SIA-Based PIM Chip Projections
39 Separate IMAGE * Separate HTML Silicon Area for a Teraflop
40 Separate IMAGE * Separate HTML Parallelism
41 Separate IMAGE * Separate HTML Petaflop PIM System Size
42 Separate IMAGE * Separate HTML Power Projections (Logic)
43 Separate IMAGE * Separate HTML Power Per Sq. Cm
44 Separate IMAGE * Separate HTML 3D Stacking
45 Separate IMAGE * Separate HTML Potential PIM Cube
46 Separate IMAGE * Separate HTML Potential PIM Cube
47 Separate IMAGE * Separate HTML Further Work: Hardware
48 Separate IMAGE * Separate HTML Further Work:Algorithm Development
49 Separate IMAGE * Separate HTML Further Work: Software Development
50 Separate IMAGE * Separate HTML Current ND PIM Work In Progress
51 Separate IMAGE * Separate HTML Conclusion

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