Shreyas Balakrishna shreyasbharath

People

`:bowtie:`	😄 `:smile:`	😆 `:laughing:`
😊 `:blush:`	😃 `:smiley:`	☺️ `:relaxed:`
😏 `:smirk:`	😍 `:heart_eyes:`	😘 `:kissing_heart:`
😚 `:kissing_closed_eyes:`	😳 `:flushed:`	😌 `:relieved:`
😆 `:satisfied:`	😁 `:grin:`	😉 `:wink:`
😜 `:stuck_out_tongue_winking_eye:`	😝 `:stuck_out_tongue_closed_eyes:`	😀 `:grinning:`
😗 `:kissing:`	😙 `:kissing_smiling_eyes:`	😛 `:stuck_out_tongue:`

This can reduce files to ~15% of their size (2.3M to 345K, in one case) with no obvious degradation of quality.

ghostscript -sDEVICE=pdfwrite -dCompatibilityLevel=1.4 -dPDFSETTINGS=/printer -dNOPAUSE -dQUIET -dBATCH -sOutputFile=output.pdf input.pdf

Other options for PDFSETTINGS:

/screen selects low-resolution output similar to the Acrobat Distiller "Screen Optimized" setting.
/ebook selects medium-resolution output similar to the Acrobat Distiller "eBook" setting.
/printer selects output similar to the Acrobat Distiller "Print Optimized" setting.
/prepress selects output similar to Acrobat Distiller "Prepress Optimized" setting.

Latency numbers every programmer should know

L1 cache reference ......................... 0.5 ns
Branch mispredict ............................ 5 ns
L2 cache reference ........................... 7 ns
Mutex lock/unlock ........................... 25 ns
Main memory reference ...................... 100 ns             
Compress 1K bytes with Zippy ............. 3,000 ns  =   3 µs
Send 2K bytes over 1 Gbps network ....... 20,000 ns  =  20 µs
SSD random read ........................ 150,000 ns  = 150 µs

Read 1 MB sequentially from memory ..... 250,000 ns = 250 µs

"In our study of program design, we have seen that expert programmers control the complexity of their designs with the same general techniques used by designers of all complex systems. They combine primitive elements to form compound objects, they abstract compound objects to form higher-level building blocks, and they preserve modularity by adopting appropriate large-scale views of system structure. In illustrating these techniques, we have used Lisp as a language for describing processes and for constructing computational data objects and processes to model complex phenomena in the real world.

However, as we confront increasingly complex problems, we will find that Lisp, or indeed any fixed programming language, is not sufficient for our needs. *We must constantly turn

	[mergetool]
	prompt = false
	keepBackup = false
	keepTemporaries = false

	[merge]
	tool = winmerge

	[mergetool "winmerge"]
	name = WinMerge

	#
	# STL GDB evaluators/views/utilities - 1.03
	#
	# The new GDB commands:
	# are entirely non instrumental
	# do not depend on any "inline"(s) - e.g. size(), [], etc
	# are extremely tolerant to debugger settings
	#
	# This file should be "included" in .gdbinit as following:
	# source stl-views.gdb or just paste it into your .gdbinit file

	Latency Comparison Numbers (~2012)
	----------------------------------
	L1 cache reference 0.5 ns
	Branch mispredict 5 ns
	L2 cache reference 7 ns 14x L1 cache
	Mutex lock/unlock 25 ns
	Main memory reference 100 ns 20x L2 cache, 200x L1 cache
	Compress 1K bytes with Zippy 3,000 ns 3 us
	Send 1K bytes over 1 Gbps network 10,000 ns 10 us
	Read 4K randomly from SSD* 150,000 ns 150 us ~1GB/sec SSD