[pypy-svn] r3773 - pypy/trunk/doc/funding

hpk at codespeak.net hpk at codespeak.net
Mon Apr 5 15:54:09 CEST 2004


Author: hpk
Date: Mon Apr  5 15:54:09 2004
New Revision: 3773

Modified:
   pypy/trunk/doc/funding/B6.0_detailed_implementation.txt
Log:
rewrote the B6.0 with respect to WP11 

please verify



Modified: pypy/trunk/doc/funding/B6.0_detailed_implementation.txt
==============================================================================
--- pypy/trunk/doc/funding/B6.0_detailed_implementation.txt	(original)
+++ pypy/trunk/doc/funding/B6.0_detailed_implementation.txt	Mon Apr  5 15:54:09 2004
@@ -423,23 +423,20 @@
 
 The PyPy interpreter as developed in Phases 1 and 2 will be particularly
 suitable to be adapted to extremely diverse runtime environments, from
-embedded devices to number-crunching machines. In WP11_ we propose to study to
-specific case of embedded devices, which are often limited in processor speed
-and memory size.  This either limits the power of software that is implemented
-for these platforms, or enforces use of low-level approaches like C/C++ or
-Java. PyPy is especially suited to support such platforms, since it can
-produce effective and compact code, while retaining the abstraction and
-ease-of-use of Python.
-
-Based on the specific needs of these devices, we will experiment with memory-
-or battery-efficient implementations of all the customizable aspects described
-in Phase 2. The PyPy code generator will need an extra platform specific
-support module, as well as interfaces to necessary device drivers. It may make
-sense to develop a PyPy simulator for the target platform.
-
-We will use feedback from actual hardware to compare the results obtained. If
-code space permits we will implement heuristics to switch to the most
-efficient implementations when these are context- or application-dependent.
+embedded devices to number-crunching machines. 
+
+In WP11_ we propose to study to specific case of embedded devices, which
+are often limited in processor speed and memory size.  This either
+limits the power of software that is implemented for these platforms, or
+enforces use of low-level approaches like C/C++ or Java. PyPy is
+especially suited to support such platforms, since it can produce
+effective and compact code, while retaining the abstraction and
+ease-of-use of a Very-High-Level Language.  Based on the specific needs
+of these devices, we will experiment with memory- or battery-efficient
+implementations of all the customizable aspects described in Phase 2.
+Additionally, results from WP13_ and feedback from a selected industrial
+partner will be used to verify the applicability of Python's flexible
+architecture for embedded devices in particular. 
 
 
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