PPT-Variability.org Aging-Aware Compiler-Directed VLIW Assignment for GPGPU Architectures

Abbas Rahimi Luca Benini Rajesh K Gupta UC San Diego University of Bologna Micreldeisuniboit MultiTherman AgingAware CompilerDirected VLIW Assignment for GPGPU Architectures . We call the tail of the head of and uv the ends of If there is an edge with tail and head then we let uv denote such an edge and we say that this edge is directed from to Loops Parallel Edges and Simple Digraphs An edge uv in a digraph is a Tuck-Boon Chan, Wei-Ting Jonas Chan and Andrew B. Kahng. VLSI . CAD LABORATORY, UC San Diego. Outline. Introduction: BTI Aging and AVS. Signoff Problem. Observations and Proposed Heuristics. Experimental Results. Jared . Coplin. and Martin . Burtscher. Department of Computer Science. 1. Introduction. GPU-based accelerators. Used in high-performance computing. Spreading in PCs and handheld . devices. 2. Power Characteristics of Irregular GPGPU Programs . Nuno Lopes . and. José Monteiro. Deriving preconditions by hand is hard; WPs are often non-trivial. WPs derived by hand are often wrong!. Weaker preconditions expose more optimization opportunities. Computational . Exascale. Workshop. December 2010. Dan Quinlan. Chunhua. Liao, Justin Too, Robb . Matzke. , Peter . Pirkelbauer. Center for Applied Scientific Computing. Lawrence Livermore National Laboratory. Ned Bair . US Army Corps of Engineers Cold Regions Research and Engineering Laboratory. Earth Research Institute, UC - Santa Barbara. AVPRO. 9-10AM 2/27/14. 1. Campbell. , C.: Spatial variability of slab stability and fracture properties in avalanche starting zones, M.Sc., University of . Graphics Processing Unit (GPU). GPU is the . chip . in computer video cards, PS3, Xbox, . etc. Designed to realize the 3D graphics pipeline. Application .  Geometry  Rasterizer image. GPU development:. By Namita Dave. Overview. What are compiler optimizations?. Challenges with optimizations. Current Solutions. Machine learning techniques. Structure of Adaptive compilers. Introduction. O. ptimization . ABHINAY RAJ KALAMBUR SABARAJAN - 50133612. Guided by: Professor Sridhar . Ramalingam. Overview. Introduction. Device Aging. My work. Aging aware Instruction Set Encoding(. ArISE. ). Duty Cycle Balancing. Why is GPU in the picture. Seeking . exa. -scale computing platform. Minimize . power per operation.. Power is directly correlated to the area in the processing chips.. Regular CPU. . – what are the chip areas going into?. 2. Chapter 9 Objectives. Learn the properties that often distinguish RISC from CISC architectures.. Understand how multiprocessor architectures are classified.. Appreciate the factors that create complexity in multiprocessor systems.. . Fisica. . Nucleare. (INFN). Italy. Accelerated Computing support . in EGI-Engage. Marco.Verlato (at pd.infn.it). Task part of WP4 (JRA2): Platforms for the Data Commons. Expand the EGI federated Cloud platform with new . The Desired Brand Effect Stand Out in a Saturated Market with a Timeless Brand JFK. BOS. MIA. ORD. LAX. DFW. SFO. Presentation for use with the textbook, . Algorithm Design and Applications. , by M. T. Goodrich and R. Tamassia, Wiley, 2015. Directed Graphs. 2. Digraphs. A . digraph.