PACE Platform-Aware Compilation Environment

The PACE Project is developing an architecture aware compiler environment. Rice University is the lead site, with active participants at ET International, Ohio State, Stanford, and Texas Instruments.

Menu "ABOUT US" Begins - Skip Menu

Menu "ABOUT US" Ends

This software was produced with support from the Defense Advanced Research Projects Agency (DARPA) through AFRL Contract FA8650-09-C-1915. Nothing in this work should be construed as reflecting the official policy or position of the Defense Department, the United States government, or Rice University.

THIS SOFTWARE HAS BEEN APPROVED FOR PUBLIC RELEASE, UNLIMITED DISTRIBUTION.

Code for Software Downloads:
Resource Characterization

PACE Prototype Compiler

Polyhedral Optimizer for the ROSE Compiler (OSU)

RoseToLLVM Translator (Available from Rose Repository)

Optimization Passes for LLVM 3.0

Application Aware Partitioner

Performance Measurement, Analysis, and Attribution

Code Available by Request:

Neural Computation Modules for Non-linear Regression and Classification

PACE Project, Rice University, P.O. Box 1892, MS-132, Houston, Texas 77005 Email: pace@rice.edu

This work is funded by the Defense Advanced Research Projects Agency through AFRL Contract FA8650-09-C-7915. The opinions and findings in this document do not necessarily reflect the views of either the United States Government or Rice University.

Menu "ABOUT US" Begins - Skip Menu

Code Available by Request:

Neural Computation Modules for Non-linear Regression and Classification

Code Available by Request:

Neural Computation Modules for Non-linear Regression and Classification

Menu "ABOUT US" Begins - Skip Menu

Code Available by Request: Neural Computation Modules for Non-linear Regression and Classification

Code Available by Request: Neural Computation Modules for Non-linear Regression and Classification

Code Available by Request:

Neural Computation Modules for Non-linear Regression and Classification

Code Available by Request:

Neural Computation Modules for Non-linear Regression and Classification