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*** Product Information and Prices Stored: Dec 20, 2009 07:45:06

Spend some time to catch up on what’s been happening in Haskell this year. In this edition of the Web News, we look back on the major Haskell news of 2009. You can also read this edition in PDF form.

The Haskell Web News brings you what’s been happening with the Haskell programming language as voted by readers of The Haskell Reddit.

Community

Haskell 2010: A major event in 2009 was the release of the  Haskell 2010 standard — the first official revision to the language since Haskell ‘98, and the first result of the Haskell Prime process. The new language standard will form the core of a rolling language upgrade in coming years.

The New Logo: Along with the new language standard came a new logo for Haskell – again, the first since Fritz Ruehr’s proposal back in the day. To produce the logo, a community competition was launched, and via anonymous condorcet voting from -cafe@ members, a winner was chosen!

Hackathons go global: For the past 3 years, a series of Haskell hackathons have been held in Europe, one or two a year, as  the Hac series. In 2009, we held 4 hackathons, and for the first time, two in North America: in Portland, Edinburgh Philadelphia and Utrecht. The next Hackathon is in Zurich in March 2010.

New user groups: For a long time the Haskell community relied on conferences for our user groups. By the end of 2009 however, the Haskell user group concept has become widespread, with nearly 30 groups around the world, including ten groups in North America, and twelve in Europe, and six across Australia, Asia and South America.

Summer of Code: Haskell.org participated in the Google Summer of Code, for the fourth consecutive year. This year, Google funded development of 5 Haskell projects:   Gergely Patai to improve space profiling, Isaac Dupree to work on Haddock, Niklas Broberg on Language.Haskell, Petr Ročkai on scaling Darcs to large repositories, and Thomas ten Cate on EclipseFP. In addition, Jane Street funded a Haskell project for the first time, under the Jane Street Summer Projects series, supporting development of the Lambda Cube 3D rendering engine.

Books

Real World Haskell: a year ago, Real World Haskell was published, the first O’Reilly book on Haskell, the first Haskell book for professional programmers, and went on to win the Jolt Award for  best technical book of the year. It has since also been translated into Japanese. It was notable also for having the entire book available in pre-pub and post-pub as a wiki.

LYAH: a quirky and accessible online book was produced, Learn You a Haskell for Great Good, becoming something of an internet sensation. LYAH is set to be published in book form in 2010.

Functional Programming Fundamentals: Erik Meijer produced a 13 part video lecture series based on Graham Hutton’s Programming in Haskell, which went on to have 500k downloads in 2009.

Compilers and Infrastructure

GHC 6.12: Version 6.12 of the primary Haskell implementation, GHC, occured in 2009, with major improvements for parallel performance, support for ThreadScope profiling, dynamic linking on Linux, and with I/O libraries Unicode-aware. The improvements to parallel performance where benchmarked, and documented in the paper ”Runtime Support for Multicore Haskell“. The GHC team also published their latest status report.

An LLVM backend for GHC? In something of a tour de force, David Terei designed an LLVM backend for GHC, implemented and benchmarked it :: PDF, finding that the current code gen was competitive, but that LLVM wins out on the numeric-based loops typical in data parallel code.

Dataflow Optimizing Backend: Norman Ramsey and João Dias presented a new dataflow optimizing backend for GHC, making it easier to do some very aggressive low level optimizations late in the compilation phase.

Data Parallelism: Data Parallel Haskell progressed further, and GHC 6.12 is significantly better than prior GHC’s. The current status of the data parallel extensions to Haskell was described at the HIM.

Supercompilation for GHC? Yet more work on the optimization front, a design was developed for adding a supercompilation phase to GHC, making possible whole new classes of aggressive code transformation optimizations that were previously quite difficult.

GHC with shared libraries: Well-Typed, funded by the Industrial Haskell Group, completed the work of enabling shared libraries to be produced by GHC.  That means “Hello world” in Haskell is now only an 11k executable using GHC.

JHC progress: There was a new major release of jhc, the whole program optimizing Haskell compiler.

UHC: At the Utrecht Hackathon on April, the first release of UHC, the Utrecht Haskell Compiler was announced, a new Haskell compiler with a GRIN-based intermediate representation, which makes extensive use of attribute grammars in its construction.

Libraries and Distribution

The Haskell Platform: in 2009, a major effort was launched to provide a single “batteries included” library suite for Haskell, suiting commercial, open source and research needs. The result is The Haskell Platform, (also now available in Debian), a single installer for a complete GHC-based Haskell system, including extensive libraries. By the year’s end there had been 450 thousand downloads of the binary installers!

Hackage: Hackage is the central repository for Haskell libraries and applications, and, along with Cabal, provides a publishing, distribution, and dependency resolution system for all Haskell code. Hackage continues to grow in 2009, faster than in 2008. There have been 3500+ package updates this year, so we now have 1750 Haskell packages available on Hackage in total, up from 750 a year ago. The size of Hackage is phenomenal, as you can see when you visualize the Haskell Universe. Earlier in the year, we reached one million Haskell downloads on Hackage. November 2009 was the first month with more than 100k downloads from Hackage in a single month.

Industry

The Industrial Haskell Group: For the first time, in 2009, a consortium of companies came together to fund continued development of Haskell and its toolchain. The result is the IHG, launched earlier in the year. The initial round of funding resulted in several improvements to the ecosystem. The group is seeking to expand membership in 2010 to further consolidate the commercial strength Haskell. The Birth of the IHG was presented at the “Commercial Users of Functional Programming” workshop.

CUFP: This year’s Commercial Users of Haskell workshop was held in Edinburgh, and included talks on Real World Haskell, teleconferencing on maps in Haskell, FP at Facebook. Next year’s CUFP will be held in Baltimore.

Industrial reports: As part of Galois‘ 10th birthday, Don Stewart presented a talk at the LondonHUG on Engineering Large Projects in Haskell, celebrating a decade of use of Haskell by Galois. TypLAB, a new startup  talked about why they use Haskell. Facebook released its lex-pass tool to automate changes to a PHP codebase, by writing abstract-syntax-tree transformers in Haskell. And Starling Software described building a real time financial trading system in Haskell :: PDF. Tom Hawkin’s Atom EDSL for control systems went into production use in trucks and buses, and is starting to be used on a NASA runtime monitoring project. The Cryptol release got slashdotted. Tupil.com talked about their experiences building commercial web apps in Haskell.

Conferences

The major conferences of the year were in Edinburgh, and for the first time we have video of the entire week, including videos of the International Conference of Functional Programming,  the Haskell Symposium, the Commercial Users of Functional Programming,  and the Haskell Implementors Meeting. Hooray for Malcolm Wallace for compiling these videos.

Libraries

New IO library: the major news in libraries included a rewrite of the IO library (to support native unicode encodings on IO, in-memory IO buffers, and more). See Simon Marlow Wander Through GHC 6.12’s New IO Library.

Associated Types for Optimizations: Another popular post was on self-optimizing data structures, by Don Stewart, showing how to statically specialize the layout of Haskell container data types, improving data density and performance.

The Text Library:  A major revision of the Haskell text library was announced by Bryan O’Sullivan, giving the Haskell community a packed, unicode text type suitable for large scale unicode text processing.

LLVM adventures: One of the most interesting new libraries of 2009 was the high level LLVM bindings for Haskell. Lennart Augustsson and Bryan O’Sullivan had various adventures with it, including beating GHC (and GCC) and producing a BASIC embedded in Haskell via LLVM.

New tools

Vacuum: The biggest tools of the year included vacuum, Matt Morrow’s tool for extracting graphs of heap objects in running Haskell processes. With it you can vizualize Haskell data structures live in GHCi.

Benchmarking: Another great new tool is criterion, a library for statistically robust microbenchmarking, by Bryan O’Sullivan. You can read more about it in the release notes.

The Leksah IDE:major announcement was made at the Utrecht Hackathon: Leksah, a Haskell IDE in Haskell by Juergen Nicklisch-Franken.

ThreadScope: Finally, another key new tool addresses the problem of profiling in a multicore setting. The result is threadscope (a tool for profiling concurrent and parallel Haskell programs). ThreadScope lets you visualize graphically events in the GHC runtime system, including GC, thread migration, execution, spark activity and more. You can watch this video to see it at work.

Haskell in New Domains

Linux Kernel: Thomas DuBuisson showed us how to write Linux Kernel Modules in Haskell.

Barrelfish OS: Microsoft’s new Barrelfish OS was built on domain specific languages written in Haskell :: PDF

seL4: the first machine-verified microkernel: the Secure Microkernel Project (seL4) announced it’s major result: the world’s first formal machine-checked proof of a kernel, and they used Haskell as a key part of their development methodology.

iPhones: GHC was modified to allow native Haskell on iPhone.

Haskell for Theorem Proving: Haskabelle was released, a tool to convert Haskell source into Isabelle theory files, suitable for theorem proving activities.  A little fun with Haskabelle can be had.

Open Source

xmonad: The xmonad tiling window manager continued to be the most popular open source app on Hackage in 2009, with the xmonad 0.9 release occurring.

gitit: another significant new project is gitit, a feature-rich wiki running on top of git or darcs, with pandoc support (meaning you can write your wiki in markdown/tex/html/…)

happstack: the happstack web framework (the Haskell equivalent of Django) was in active development, with happstack 0.4 released. happstack powers gitit, and patch-tag.com, amongst other things. You can also read about why Happstack scales, and SQL fails!

darcs: the darcs revision control system world was extremely active this year, with darcs 2.2 and darcs 2.3 released (along with a Summer of code project) and great strides in scalability via a new storage mechanism.

Tutorials

The top 7 tutorials of the year:

• What monads are not
• How you should(n’t) use Monads
• Haskell: The Confusing Parts
• A Neighborhood of Infinity: Where do monads come from?
• Parallelism ≠ Concurrency
• The Typeclassopedia
• Evolving faster Haskell programs

Advocacy

And finally, the most popular pieces of advocacy for the year:

• Hello Haskell, Goodbye Lisp
• The Haskell Rabbit Hole
• Haskell is beautiful in practice
• Everyone’s talking about Haskell

Haskell 10 years ago

And the news of 10 years ago? Here’s a selection of the top news in 1999.

HaskellDB: Daan Leijen announced a preview of HaskellDB, the type safe database library for Haskell, now on Hackage.

Edison data structures: Chris Okasaki announced the first public release of Edison, a library of efficient purely functional data structures.

Functional Graphs: Martin.Erwig announced the Functional Graph Library.

Haskell 98: Simon Peyton-Jones announced that the Haskell 98 standard was done.

Hugs : Mark Jones announced a beta release of Hugs 98.

GHC 4:  Simon Marlow announced the GHC 4.02.

c2hs: Manuel Chakravarty announced the C->Haskell 0.7.2 – beta release

Craft of FP: Simon Thompson announced the Haskell: The Craft of Functional Programming: Second Edition

TclHaskell. Meurig Sage announced the TclHaskell, an FFI binding to Tcl.

This is just some of the new stuff that has happened in Haskell this year. You can stay up to date by following the Haskell Reddit. See you in 2010!

Dog in the Parallel World Orchestra – Halcion Candy
Lyrics by: Haru
Music by: Junjun

DOGin the パラレルワールドオーケストラ　「ハルシオンキャンディ」
詞：春
曲：準々

ハルシオンキャンディ
舐めて 始まるさ
狂ったパレードは
ぐるぐる廻る
ハルシオンキャンディ
舐めて さよならだ
真白い手首と 傷あげるから

ボクの祈りと音と願いが
大人の世界から隔離されるなら
キミと今すぐ首吊りをするさ
「らいらいらいらら…」

赤い糸は実在するから
願いを叫ぶよ 祈りを歌うよ
まるで全然興味はないのさ
「らいらいらいらら…」

BOW!WOW!BOW!WOW!
キミの隣で吠えたい

騒音の中 深く なら
午前３時の花を咲かすなら
傷跡の音階を 正しく登れ

BOW!WOW!BOW!WOW!
って僕ががなれば

嘘つきの世界の真ん中で
苦しくって悲しくって

ボクとキミは同じだから
カッターを握り締め

ハルシオンキャンディ
舐めて 始まるさ
狂ったパレードは
ぐるぐる廻る
ハルシオンキャンディ
舐めて さよならだ
真白い手首と 傷あげる

手を繋いだら
飛び降りも自由さ
ボクはキミと一緒に
十字を切った
症状を和らげる
飴玉をもう一つ頂戴
ブレーキを壊して
ボクはPSYCHOスマイル

赤い目の大人はボクを見た
「静寂でカーテンが揺れる」
涙目で星空をボクは見た
「決断が簡単に終わる」

手を繋いだら
飛び降りも自由さ
ボクはキミと一緒に
十字を切った
症状を和らげる
飴玉をもう一つ頂戴
ブレーキを壊して

ハルシオンキャンディ
舐めて 始まるさ
狂ったパレードは
ぐるぐる廻る
ハルシオンキャンディ
舐めて さよならだ
真白い手首と 傷をあげるから

廻る MERRY-GO-自由世界
叫んでる 叫んでる
最高の世界はこれからだ
ブレーキは壊れた
ボクはPSYCHOスマイル

ローマ字：

HARUSHION KYANDI
namete hajimaru sa
kuruttta PARADE wa
guruguru mawaru
HARUSHION KYANDI
nameta sayonara da
mashiroi tekubi wo　kizu ageru kara

Boku no inori to oto to negai ga
otona no sekai kara kakuri sareru nara
kimi to ima sugu kubitsuri wo suru sa
「rairairairara…」

Akai ito wa jitsuzai suru kara
negai wo sakebu to　inori wo utau yo
maru de zenzen kyoumi wa nai no sa
「rairairairara…」

BOW!WOW!BOW!WOW!
kimi no tonari de hoetai

Souon no naka 　fukaku　nara
gozen sanji no hana wo sakasu nara
kizuato no onkai wo 　masashiku nobore

BOW!WOW!BOW!WOW!
tte boku ga ganareba

Usotsuki no sekai mannaka de
kurushikutte kanashikutte
Boku to kimi wa onaji dakara
KATTAA nigirishime

HARUSHION KYANDI
namete hajimaru sa
kuruttta PARADE wa
guruguru mawaru
HARUSHION KYANDI
nameta sayonara da
mashiroi tekubi wo　kizu ageru

Te wo tsunaidara
tobiori mo jiyuu sa
boku wa kimi to issho ni
juuji wo kitta
shoujou wo yawarageru
amedama wo mou hitotsu choudai
BUREEKI wo kowashite
boku wa PSYCHO SUMAIRU

Akai me no otona wa boku wo mita
「seijaku de KAATEN ga yureru」
namidame de hoshizora wo boku wo mita
「ketsudan ga kantan ni owaru」

Te wo tsunaidara
tobiori mo jiyuu sa
boku wa kimi to issho ni
juuji wo kitta
shoujou wo yawarageru
amedama wo mou hitotsu choudai
BUREEKI wo kowashite

HARUSHION KYANDI
namete hajimaru sa
kuruttta PARADE wa
guruguru mawaru
HARUSHION KYANDI
nameta sayonara da
mashiroi tekubi wo　kizu ageru kara

Mawaru　MERRY-GO-jiyuusekai
sakenderu　sakenderu
saikou no sekai wa kore kara da
BUREEKI wa kowashite
boku wa PSYCHO SUMAIRU

Dog in the Parallel World Orchestra – Rainy Rain
Lyrics by: Haru
Music by: Junjun

DOGin the パラレルワールドオーケストラ　「Rainy Rain」
詞：春
曲：準々

ある晴れた夜の中　　君は泣いているかな
ある晴れた夜の中　　僕はずっと泣いていたよ

唄にすれば 腐って見えた。僕らの事が
嘘の数 と 本当の理由
わかんなくってさ　傷になって 痛いって泣いてた
凄い大事だったのに　壊したんだ

夢の中なら　もいっかい逢えるのかなって
願って　枕濡らした
逢えない事が 分かってたから
お揃いで買ったキャンドルを吹き消して
僕らは鳴らない電話を置いて祈ったんだ お互いの幸せを

淋しくって夜が まるで僕を怒っているみたい
黒い空が まるで 僕を叱っているみたい

ある晴れた夜の中　君は起きてるかな
ある晴れた夜の中　僕はずっと起きているよ

夢の中なら　もいっかい逢えるのかなって
願って　枕濡らした
逢えない事が 分かってたから
お揃いで買ったキャンドルに明りを灯して
僕らは鳴らない電話を置いて祈ったんだ お互いの幸せを

夢の中なら　ごめんねって言えるのに 眠れないよ
となりに君がいないと
淋しくってさ　見上げたら

星空がね 広がっていたんだ

星を一つ また一つ
つかんで 言葉に 変えてみたよ
そしたら 言えた

こんな唄になってた。

ローマ字：

Aru hareta yoru no naka　kimi wa naiteiru kana
aru hareta yoru no naka　boku wa zutto naiteita yo

Uta ni sureba kusatte mieta. Bokura no koto ga
uso no kazu　to　hontou no riyuu
wakannakute sa　kizu ni natte　itaitte naiteta
sugoi ookoto datta no ni　kowashitanda

Yume no naka nara　moikkai aeru no kanatte
nagatte　makura merashita
aenai koto ga　wakatteta kara
osoroide katta CANDLE wo fukikeshite
bokura wa naranai denwa wo oite inottanda　otagai no shiawase wo

Sabishikutte yoru ga　maru de boku wo okotteiru mitai
kuroi sora ga　maru de　boku wo shikatteiru mitai

Aru hareta yoru no naka　kimi wa okiteru kana
aru hareta yoru no naka　boku wa zutto okiteiru yo

Yume no naka nara　moikkai aeru no kanatte
nagatte　makura merashita
aenai koto ga　wakatteta kara
osoroide katta CANDLE ni akari wo akashite
bokura wa naranai denwa wo oite inottanda　otagai no shiawase wo

Yume no naka nara　gomennette ieru no ni　nemurenai yo
tonari ni kimi ga inai to*
sabishikutte sa　miagetara

Hoshizora ga ne　hirogateitanda

Hoshi wo hitotsu　mata hitotsu
tsukande　kotoba ni　kaete mita yo
soshitara ieta

Konna uta ni natteta.

*I don’t think this line is sung

On December 9, 2009 CloverETL Cluster Edition was launched at PriceWaterhouseCoopers premises. CloverETL Cluster intelligently partitions data and distributes them evenly across multiple nodes in a cluster for execution in parallel. CloverETL Cluster’s ability to load balance large data transformations increases throughput, fault tolerance and flexibility.

CloverETL Cluster can be deployed on premise in a customer’s own data center or in a variety of cloud configurations, such as Amazon EC2, which can drive costs even lower. During the launch in Prague, CloverETL Cluster was demonstrated running on four Amazon EC2 servers.

The following table shows the time CloverETL requires to execute a moderately complex transformation of six million records (725 MB) in a variety of local and cloud configurations:

• CloverETL Desktop Designer on a MacBook: 150 seconds
• CloverETL Cluster Load Balanced Across Two EC2 servers: 60 seconds
• CloverETL Cluster Load Balanced Across Three EC2 servers: 43 seconds
• CloverETL Cluster Load Balanced Across Four EC2 servers: 31 seconds

summary of Forest Day 3 [html] Martin Parry.Imperial University.London. Call for:Marshall Plan
Martin Parry – Imperial University “Key Factors”
Posted by Wordmobi

Author : GUITONO, LIBRANTO

Tugas Akhir ini mempelajari vacuum tube dan karakteristiknya dengan tujuan supaya dapat mendesain rangkaian power amplifier vacuum tube dengan konfigurasi paralel yang mempunyai frekuensi respon 15Hz-20kHz dengan daya output 10Watt rms. Power amplifier ini menggunakan trioda 6H1N, pentoda EL34 dan menggunakan common cathode sebagai desain rangkaiannya. Pada desain rangkaian diharapkan power amplifier ini mempunyai frekuensi respon 15Hz-20kHz dengan penguatan daya sebesar 10Watt rms tetapi dari hasil pengujian pada frekuensi respon 15Hz-20kHz menghasilkan penguatan daya sebesar 7,263Watt rms. Hal ini disebabkan karena besar impedansi output primer pada transformator output yaitu 1553,125 . tidak sesuai dengan impedansi output pada power amplifier yaitu 68,6665 .. Besar efisiensi daya dari power amplifier vacuum tube dengan konfigurasi paralel ini adalah 28,32%.

Keyword : vacuum tube, power amplifier, parallel, triode, pentode

Sumber : http://repository.petra.ac.id/874/

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6ft Ieee 1284 Bc Parallel Printer Cable Microcent36m/cent36m Overview

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6ft Ieee 1284 Bc Parallel Printer Cable Microcent36m/cent36m Specifications

*** Product Information and Prices Stored: Dec 11, 2009 04:45:06

For OLTP, oracle has been proved to be the best choice regarding the performance and scalability, exadata just enhances its leadership in this direction. But for data warehouse, could exadata compete and succees against teradata by supporting more IOPS, larger cache and interconnect throughput?

Teradata has the built-in parallelism and it’s cheaper to run in parallel because of it’s share nothing architecture as there is less coordination overhead. For oracle to run in parallel, slaves in different slave sets have to exchange message. The total memory for exchanging message is X*degree*degree*parallel_execution_message_size. X is 3 for non-RAC and X is 4 for RAC. Huge teredata databases could have more than 2,000 nodes. To get oracle reach the same parallelism, how much memory does oracle need to exchange message between slaves? If set parallel_execution_message_size to 64K, the maximum size we could set (for large query,  the more parallel_execution_message_size the better), so oracle needs 3*2000*2000*64k=768G memory for non-RAC,  or 4*2000*2000*64k=1T memory for RAC.  Typically exadata is used as RAC, so it needs 1T memory purely for message exchange. And what’s the overhead of manage this 1T memory? I have no box to test it out.  Another problem is that when the producer generates message faster than the consumer consumes the message, then the buffer (parallel_execution_message_size) for message will be full, and the producer has to wait until there are free space in the buffer. This a not problem if producer is always faster than consumer, but it’s a problem if sometime producer is faster and sometime consumer is faster.

At any time at most two slave set can work at the same time, and each slave set works for the same step in an execution plan,  if a sql runs in degree of 1000 and one slave is slow,  all other 999 slaves have to wait for it to complete before execute the next step. For a hash join with 10 tables,  totally we have 9 joins, each join will complete until the slowest slave completed. Oracle doc suggests to use denormalized for data warehouse, and teradata doc said denormalization is not needed as join in teradata is cheap. Do you like denormalization? More often than not, we have to do the denormalization because of performance issue, if the performance is not a problem, why use denormalization?

If not use partition table, oracle has to hash every row in the table to know which slave the row should go to, if use partition table AND the join column is the partition key, then oracle could use partition wise join or partial partition wise join, in this way oracle doesn’t need to hash every row. Teradata also has to distribute the rows in one node to other nodes if the join column is not the primary index (which is used to determine which node the row should sit in), but the mechanism behind is simple and efficient: distribute the rows in one node to all others node based on the join column and put distributed rows in a pool, there is no limit as parallel_execution_message_size in oracle. The pool teradata used is just like temporary tablespace which needs physical IO to perform against it,  you might say memory is faster than disk, but for large query, who expects the data could be cached fully in memory?

“Michio Kaku, leading physicist, reveals the startling and indeed frightening future of the internet: how it will become the equivalent of the ‘magic mirror’ of fairytale fame, even able to find your perfect match. Although he admits to Lisa Dwan that computers will never have the ability of intuition, they will be able to ‘read minds’ in the future. He also speaks on parallel universes, nuclear weapons, the loss of the North Pole, and God.”

He is blowing her mind
1

2

Sunday December 6, 2009 By Kevin Morrow

Okay so here’s where caramel is in this candy bar of a topic. When I think about life I think about three things: the spirit, the mind, ans the body. I believe that the mind (thoughts, subconscious mind) and the spirit exist outside of time.

I know my thoughts rocket around faster than my body, and I know they aren’t physical like my body. So it’s my belief that both the mind and the spirit exist outside of the time concept.

I think that “time” is an “IDEA” and we experience variables of that “idea” in the forms of bodies and other material things.

When I’m dreaming I observe from a point of view that ignores time. I can move how I want, when I want, and where I want. I’m actually like a time alchemist in my dreams. I frequently maneuver like Neo in the matrix. And if I say “like” one more time I might have to stop writing this blog. Just kidding.

In my dreams I can look at things from all sides at once. As if I am all awareness at once…

This made me think. If time travel were ever possible, and I believed in their being one mind, I could actually use my mind as a time machine. It already is, it recalls the past, and predicts the future, and it operates in the present at the same time. Sounds like a time traveler to me.

Imagine that there are parallel universes in which you are you in every possible variation. This isn’t far-fetched, this is what you are at any given moment. Your body is always changing, and every choice you make sets a new tangent of possibilities in motion.

Imagine you can go into your mind and communicate with your other selves. May sound psycho… but remember that you’re talking to yourself right now as you read these words.

Perhaps you are a psycho lol…In that case maybe you shouldn’t tell me about that…

I yoke, I yoke (oops I mean joke), laugh…it will make you smile.

Back to the subject…

Your (and my) mind can recall memories that may or may not be true. So why wouldn’t it be able to access parts of itself that aren’t being used? What’s stopping it from using those ingenious characteristics that you know you possess? Read Are You Holding On To True Memories for more info on that.

The fact is, there are parallel universes. There are parallel realities. We (you and I) make choices in reality that lead us in certain directions. At any moment we can choose to go in infinite directions. It’s the material world that has a lag time between the thoughts and the material existence of the thoughts.

So…young Skywalkers…use the force. Inside of your mind you can time travel to what ever version of yourself you want. You can actually talk to any version of yourself and absorb that mindset. You already talk to yourself, even publicly sometimes. Don’t lie, I know you do haha.

That’s the “IDEA”. Time Traveling is the “IDEA.” The machine is the variable. Think about it.

When you watch yourself on a video, you are consciously time traveling. You can learn from your past self when looking at a video. This concept is not far-fetched. It’s just transcending the need for a camera and or machine, and just using your mind.

You could even film yourself saying things you want to accomplish in a day. Then re watch the video to see what you actually accomplished, and study your mind state as you do this. But as you make the video, your mind is projecting into the future in a reality that is time jet lagged. Chew on that. Hungry? Grab a snickers! That’s a $100,000 plug-in right there.

Sincerely,

-Kevin

Perhaps the worst possible way to transmit video would be to send all pixel data in parallel.  That’s exactly how [Gebhard Sengmüller's] parallel image device works. To be fair, this is an art piece called “A Parallel Image” that addresses the concept of where we would be if serial data transmission had never come to fruition. The brochure (PDF) accompanying the exhibit gives the juicy details we’re always looking for.

The device consists of a photo sensor unit and a display unit. Both are one-square-meter stripboard panels made of epoxy. The sensor unit consists of a 50×50 grid of photo-conductors that have their counterparts in the 50×50 grid of light bulbs on the display unit. Things start to get pretty crazy when you throw in the 7500 meters of magnet wire that connect the 2500 pixel sensor unit to the display unit.

You should be able to put together how this works. The sensors pick up light and then effect the brightness of the corresponding light bulbs. The result is an interesting image, and a nightmare of wire porn that would drive any TV repairman to drink.

Tomorrow there is a test

We have a huge partition table (25 partitions) on db1, and need to copy it to another database db2. The straightforward way I could think of is to insert in parallel over network. So run the command on db2:

insert /*+ append parallel(a,4) */ into tab1 a select /*+ parallel(b,4) */ * from tab1@db1;

At the remote DB side db1, I could see 4 slaves are waiting for “PX Deq Credit: send blkd”, and the coordinator is waiting for “more data to client”.  That means 4 slaves are waiting for the coordinator to consume the data, and the coordinator is waiting for data to be transferred over network. The bottleneck here is the network. To improve the transfer speed over network, I need kick off more non-parallel sql instead of 1 sql with parallel.

For a partition table with 25 partitions, if I use 5 separate non-parallel sql (each load 5 partitions) to load the data , then we could have 5 inter-database connections instead of 1 inter-database connection, in this way we could get better network throughput.  (I believe there is a upper limit on the transfer date rate over sql*net even if there are LOTS of free network bandwidth, I have ever logged a tar about how to tune sql*net but didn’t get satisfied answer)

So what need to do is:

1: Remove the hint of parallel(b,4). This hint is of no use, because the speed to read the data from the table is quicker than the speed to send the data to network. FTS is not the bottleneck.

2: one sql statement inserts data from one partition, and kick off 5 sessions, each session run 5 of the following sql.

insert /*+ append  */ into tab1 a select * from tab1@db1 partition (part00);
insert /*+ append  */ into tab1 a select * from tab1@db1 partition (part01);
insert /*+ append  */ into tab1 a select * from tab1@db1 partition (part02);
insert /*+ append  */ into tab1 a select * from tab1@db1 partition (part03);
…………………
insert /*+ append  */ into tab1 a select * from tab1@db1 partition (part24);


After the change, the data transferred per second increases a lot,