From 28efd886445a3d8bbc4c2d680b49ddeacbd7a549 Mon Sep 17 00:00:00 2001 From: TimothyLottes Date: Wed, 9 Nov 2016 18:21:59 -0500 Subject: [PATCH] Add files via upload --- 20161011.html | 78 +++++++++++++++++++++++++++++++++++++++++++++++++++ index.html | 3 +- 2 files changed, 80 insertions(+), 1 deletion(-) create mode 100644 20161011.html diff --git a/20161011.html b/20161011.html new file mode 100644 index 0000000..5781910 --- /dev/null +++ b/20161011.html @@ -0,0 +1,78 @@ +
+

20161011 - Forth Hardware Thoughts

+
+ +James Bowman's FPGA based J1 : +Site | +PDF | +Presentation | +Forth Source +
+ +Chuck Moore : +Arithmetic | +Instruction Set | +Ether Forth | +Problem Oriented Language +
+
+ +GA144 +
+GreenArrays
+144 cores
+9216 18-bit words of memory
+21.3 mm^2 area on 180 nm process
+0.65 watts at peak
+666 MHz peak instruction rate +
+
+At 180 nm, roughly 20 GA144s would fit in large GPU area: 144 cores * 20x = 2880 cores
+At 180 nm, roughly 380 GA144s would fit in large GPU 250 watt budget: 144 cores * 380x = 54,720 cores
+At 28 nm, assuming 40x smaller area than 180 nm, in large GPU die: 144 cores * 20x * 40x = 115,200 cores
+115,200 cores * 64 words/core = 7,372,800 18-bit words of memory +
+
+GA144 runs async, but has a peak instruction rate which is roughly 3x higher than GPUs of the 180 nm era +(based on wikipedia numbers). + +The point of this thought experiment +was to roughly imagine how a forth based machine would scale in an alternative timeline +where they had been commercially successful. +Seems possible to scale to over 100 K cores on 28 nm. +These forth cores don't directly compare to GPU cores. +For example, GA144 38-bit multiply result takes 18 +* operations: +115,200/18 = 6400 multiplies/clock, +and forth designed around rational math instead of floating point. +Seems possible that in terms of raw arithmetic, the forth machine would be competitive, +if problems were solved in a "parallel forth" way. +However, in terms of programmable logic, +the forth machine would likely be over an order of magnitude faster. +Modern machines tend to use area and pipelining to make expensive operations (like multiply add) run fast, +while GA144 effectively micro-codes them, +keeping low area and much higher throughput for inexpensive operations. +
+
+The imaginary scaled GA144 memory capacity looks possible for a high ALU/MEM ratio. +Note GA144 only has 64 words of memory per core. +Working this from a different perspective, the Epiphany V is 64 MB of on-chip memory. +That 64 MB divided across 256 K forth sized cores is again only 256 bytes of memory (or 64 32-bit words/core). +Point being, if one wanted to scale to massive counts of simple cores, +memory/core has to be tiny. +
+
+Which brings up the ultimate question: +is it possible to practically leverage the order of magnitude increase in performance for simple operations, +when one needs to deconstruct every problem into such small tasks? + + + + + + + + +
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20161108 - Archive

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20161109 - Archive

 

 
In progress moving blog again, this time to Github Pages ...

 

@@ -51,6 +51,7 @@ Below this is active random migration (456 prior posts still to filter through)
 20161014 - Possible Directional Routing Hoplite Variant?

 20161013 - SymbOS - 8-bit OS Awesome Sause

 20161012 - Technical Evaluation of Traditional vs New "HDR" Encoding Crossed With Display Capability

+20161011 - Forth Hardware Thoughts

 20160715 - LED Displays

 20160127 - Temporal AA Neighborhood Clamp