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Carl Zeiss 1.4/35 Distagon T* Review
Despite strong roots in photojournalism, the Nikon F system somehow failed to maintain a stable of modern fast wide-normal lenses for most of its history. The landscape changed dramatically when, in the middle of 2010, Nikon users suddenly found themselves with choices of fast wide-normals to suit almost every budget and shooting style. The Zeiss Distagon in this review is the most controversial among these new options.
The high-speed Distagon is a new formula designed as much for high sharpness in the plane of focus as smooth un-sharpness outside. The result of the design process was a surprisingly large optical cell, chosen for reasons of cost probably. In addition to that the lens was equipped with a complex focusing mechanism – seemingly based on metal cams – whereby front and rear elements move at different and non-linear rates. Combining these two features leads to a very large and very heavy lens even for the specification.
As soon as the 1.4/35mm ZF lens was announced it was obvious to me (and my wife) that I would eventually try or directly buy it. The slower 2/35mm ZF was my introduction to prime lenses, to the manual focus ethos and was pivotal in helping me shape my way of seeing photographs. The promise of a "grown up" implementation of my favorite and most-used lens with a boost of speed and improved resolving power in the near-field made my adopting it seem like a no-brainer. In the end I did purchase the high-speed Distagon, but quickly decided to return it for a refund.
The f/1.4 Distagon is a very large and heavy lens; it is even heavier than it looks, it is just shockingly heavy. The build quality of this lens is also a clear notch above the simpler and older Zeiss ZF's like the f/2 Distagon. Mounted on the D700, the pair handle roughly the same as the D700 did with the 24-70mm zoom when I tested it (I disliked that combination for its size and weight).
Manual focus is neither slow or fast with this lens, the pitch feels just about right, but the task is considerably more difficult than it was with the 2/35mm lens. For action/portraiture the camera's built-in rangefinder is an invaluable help, but on my camera the lens required a substantial amount of back-focus correction before I could use it. Luckily one can concentrate on the act of focusing without being distracted by the mechanism implementation because this is probably the smoothest-focusing of the Zeiss ZF lenses. Despite what I believe is a complex focus mechanism, the resistance is almost perfect and almost perfectly even throughout the range.
The fast Distagon extends only slightly while focusing.
This lens introduced me to the ZF.2 family, with their slightly different aperture rings and functions with the camera. Here lied a major disappointment however, as the lens sample I acquired incorrectly translated camera settings to the physical aperture. Every aperture selected translated to an aperture that was 1/2 a stop too wide, which lead to overexposure at a minimum and also not the artistic result I desired. My salvation here was a D700 option to switch away from computer-defined aperture and only use the aperture ring, as if it were a ZF.1.
This 1.4/35mm is a good performer on any basis but it doesn't exactly displace the slower 2/35mm, which has garnered an exceptional reputation over the years. This lens is as sharp as anyone needs it to be however. This is the first f/1.4 lens I think I could use at full aperture with impunity.
This high-speed Distagon is a very sharp lens even at full aperture when properly focused. Fine detail is rendered with average micro-contrast on-axis at this aperture, and more coarse detail in the outer zones. Global contrast is on a very high level especially considering other lenses in the class. The combination of smooth bokeh (sometimes), high global contrast, vivid colors and fine detail in the plane of focus lends impact to images made by the fast Distagon.
In the limited time I spent with the lens I used it very little at the smaller apertures. I limit my comments on small-aperture performance to stating that it looked fine. The appeal of this lens doesn't lie there.
One rarely mentioned and ironic fact of Bokeh is that it is rarely very good on fast lenses. Bokeh quality is strongly affected by astigmatism and mechanical vignetting of the circle of confusion, both of which are associated with fast lenses. In the case of this Distagon the Bokeh is OK, one might say it is good if one qualifies that with "for a lens wider than 50mm". It is certainly very beautiful when backgrounds are distant or contain only low-frequency detail, particularly thanks to the high contrast and vivid colors, but near the plane of focus there can be more nervousness and halation than smooth blur.
Chromatic aberrations could be an issue for some. Longitudinal chromatic aberration, particularly, is often significant even in normal use, because all strong highlights clad themselves in green and magenta outlines. See the samples section for an example.
Like other Zeiss T* lenses the 1.4/35mm ZF shows strong resistance to veiling flare when shooting against the light. In fact it is simply outstanding in this area, despite the handicap of large elements. At full aperture, and staring directly into the illuminant, contrast is maintained all over the frame and up to the border of the light itself.
The 1.4/35mm Distagon ZF is as good a lens as one should hope it to be. It may not live up to the hype of marketing or the unreasonable expectations of some enthusiasts but it is a really fantastic lens. In theory this lens would be bliss to shoot but I didn't enjoy it, I kept thinking that I'm done playing with large and heavy lenses.
Would I recommend this lens to other photographers? I don't know. My deflated enthusiasm might mean that my conversion to a rangefinder shooter is now complete.
Hello Olivier,
I share your comment & thought. I have not tried this new lens & am contemplating to get one. I do have the concern on 35mm F1.4's worth since I am also using the 35mm F2.0 ZF now. Though I am not totally satisfied with 35mm F2.0 as I think the color is rather too punchy & its handling in low light is less effective than 28mm F2.0 (see your reply to me earlier on 28mm F2.0. In fact, I returned the 28mm & get the 35mm instead as I feel that 35mm is better in day to day application). I do mind this heavier option as I really dislike the D700 & 24-70mm F2.8 combo. Your review does help me not to pursue this route. I now have the 100mm F2.0 Makro & I think if I want better color rendition & sharpeness, I will go for the 21mm F2.8 ZF instead.
Thank you again!
Very nice review again, Oliver!
And, having a handful of ZF's myself along with a rangefinder set, I notice the same natural trend towards disliking the D300/ZF combo's and liking the rangefinder combo's.
Size does matter! And the recent stream of mirror-less camera's show this clearly.
A bit sad as I really love the ZF lenses. But I think my next lens will not be the 21/2.8 or the 28/2.0 or the 35/1.4 but the 50/1.5 (Sonnar)…
Thanks for posting this review Olivier!
I've been waiting patiently for this one, and to be honest from what you've written I don't feel I'm missing out by sticking with my 2/35 zf.2, which is becoming one of my all-time favourites (and was purchased because of your review!).
On a side note, I do wish Zeiss made a version of their 50mm Sonnar for the F mount, as I prefer it's rendering to the Planar. Maybe one day 🙂
I am currently looking to purchase either the 35 f/1.4 or the f/2.0 and wanted to know more about their comparison. I know that weight might be an issue for some, but if we are to disregard weight as a factor, does the f1.4 improve that much over the f2.0? Thank you!
Hi, Olivier.
I'm quite happy I was lucky to find your photo blog and zeiss lenses reviews in particular.
Could I ask one question corresponding a large and heavy Zeiss ZF 35/1.4 lens? You have a lot of photo gear options to choose from (rangefinders, DSLRs) so your opinion is to be unbiased. Finally do you miss ZF 35/1.4? Do you want to reaquire this lens? Is its weight and bulk justified by its unique drawing style?
Actually I'm in search of a zeiss lenses set up for FF and close to choose 21D, 35/1.4 and 100MP so your experienced ponit is quite valuable.
Best regards, Alex.
Carl Zeiss Jena Flektogon MC 35mm f/2.4 is a very solid lens. The lens shows some weakness around borders at wide aperture settings, especially on a FF camera, but again, I have yet to see a wide angle lens that doesn't struggle here. Overall, this lens can easily compete with Carl Zeiss Distagon (C/Y) T* 35mm f/2.8 for your attention and bucks. One major advantage that could be quite valuable to some photographers is the close minimal focusing distance – it is actually shorter then on some dedicated macro lenses! Of course, all this assumes that you're OK using a fully manual lens.
I own the Canon (ZE) version of this lens and use it on a 6D. I'm also a rangefinder shooter and use the Leica M-E and M Monochrom (original).
This lens on a DSLR, even a light one like the 6D is a beast. It is big, heavy and would not be my first choice for a long day walking. What it is, however, is magical in its rendering. It is sort of an anti-rangefinder sort of lens, as when I shoot with a rangefinder camera I tend to the smaller and lighter (not to mention slower) lenses. At 35mm I shoot the Leica 35mm f/2.5 Summarit, and wouldn't think of putting an f/1.4 Summilux or f/1.4 Distagon on my M cameras. While the Fast RF lenses are smaller and lighter than SLR lenses like this Zeiss, thy are still big and heavy by RF standards and make me think that I may as well carry my SLR.
The other big disadvantage of RF cameras and lenses is close focusing. I love close focusing at wide apterture on a 35mm lens, but even the $5000+ Leica Summilux just won't do it.
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Live updates
Ex Gills player awarded nearly seventy thousand pounds in compensation
The former Gills FC player Mark McCammon has been awarded £68,728.42 plus costs at a hearing in Ashford after a tribunal ruled he had been subject to racial victimisation.
Gillingham Football Club's new manager
Martin Allen is unveiled as the new manager of Gillingham Football Club as they face being ousted from their training ground for unpaid bills. Click above for the full report
Martin Allen confirmed as new Gills manager
The former Barnet and Brentford boss has been unveiled as the new manager of Gillingham football club at a press conference.
Speculation mounts over new Gills manager
Martin Allen is widely expected to be named as the new Gillingham manager later this afternoon.
Reports circulating this morning claimed the former Barnet and Brentford boss was on his way to Kent to be unveiled at a press conference at Priestfield at 4pm.
Allen was in charge at Underhill for a three-game spell at the end of last season and oversaw two wins in that stay, including a final day victory which kept Barnet in the League.
- ITV Report
Fan convicted of disorder
Gills fans banned from club's next game
A row has blown up between Gillingham football club and Kent police about how many officers will be needed at the game against Swindon. The two clubs are fierce rivals and tensions are expected at the match on April 21st. Now fans are facing a ban as Sarah Saunders has been finding out.
Kent Police react to Gills fans ban
Kent Police has said plans to hold a match between Gillingham and Swindon behind closed doors is justified.
Chief Superintendent Alasdair Hope, of Kent Police, said: "The safety of fans attending this football match is our main priority and we are not prepared for their safety to be compromised.
"The provision of an appropriate number of police officers inside the stadium is essential, and the cost of this must be met by Gillingham FC.
"To expect Kent Police and the tax-payer to subsidise a commercial event is not acceptable. Commercial enterprises across the country pay for the policing of their events, including football matches, and no one is exempt."
- ITV Report
Gills match to be played behind closed doors
Council prohibition order means match will be played in empty ground
Councillor Mike O'Brien, of Medway Council, said: "We have unfortunately been left with no alternative but to issue a prohibition notice on the game preventing supporters from attending."
The match between Gillingham and Swindon is due to be played on April 21.
He said the prohibition order was as a result of a dispute between Gillingham FC and Kent Police about costs and the number of officers needed to police the match.
Police funding row sees fans banned from Gills
Fans will be banned from attending a match between Gillingham and Swindon match following a row with Kent Police over funding.

subset: commoncrawl


text: TabsReferenceDictionaries, Directories, Handbooks, Encyclopedias, etc. - Reference works are useful when you need to obtain quick facts, define the terms and scope of your search, or get a broad overview of a topic. Best Bets! are marked with a.Products available to registered McMaster Students/Staff/Faculty Only are marked with a .Atlases & Maps Concise historical atlas of Canada Mills Maps (1st floor) G 1116 .S1C66 1988 Historial atlas of CanadaMills Library (multiple locations) G1116 .S1 H58 Early Canadian maps: The W.H. Puglsey Collection Mills Maps (1st floor) ZG 3400 .M45 1998 or Online Bibliographies Bibliographia CanadianaMills Bookstacks ZFC 51 .T57 Bibliographie de l'histoire du Quebec et du Canada Mills Reference (2nd floor) ZFC 164 .A82 Canadian history: A reader's guide Mills Reference (2nd floor) ZFC 164 .C36 Canadian military experience, 1867-1995: A bibliography Mills Gov Pubs (2nd floor) CA1.. 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Pumpkin Pie Pudding
This light and delicious pudding topped with candied walnuts and whipped cream tastes just like pumpkin pie! I was really excited when I opened up my new cooking light magazine and saw this recipe. I mean come on, You know how much I love pumpkin! 😉 As I was enjoying this scrumptious dessert I kept thinking of how awesome crushed gingersnaps would be on top. Sadly I had none, but when I make this again I will definitely add some!
Pumpkin Pie Pudding
This light and delicious pudding topped with candied walnuts and whipped cream tastes just like pumpkin pie!
Yield: 4 servings
1/2 cup sugar, divided
2 tablespoons cornstarch
1 3/4 cups 1% milk
1 large egg
1/2 cup canned unsweetened pumpkin
1 teaspoon vanilla extract
1/2 teaspoon ground cinnamon
1/8 teaspoon salt
1/8 teaspoon ground nutmeg
Cooking spray
1/4 cup chopped walnuts
Dash of salt
1/4 cup heavy whipping cream
Combine 6 tablespoons sugar and 2 tablespoons cornstarch in a medium saucepan over medium heat. Combine milk and egg, stirring well with a whisk. Gradually add milk mixture to sugar mixture, stirring constantly, and bring to a boil. Cook for 1 minute, stirring constantly. Remove from heat.
Combine pumpkin and the next 4 ingredients (through ground nutmeg) in a bowl, stirring well. Slowly add pumpkin mixture to milk mixture, whisking constantly. Place pan over low heat, and cook for 3 minutes or until thoroughly heated, stirring constantly (do not boil). Divide pudding evenly among 4 dessert bowls, and cover surface of pudding with plastic wrap. Chill.
Line a baking sheet with foil, and coat foil with cooking spray. Place the remaining 2 tablespoons sugar, walnuts, and a dash of salt in a small nonstick skillet; cook over medium-low heat until sugar dissolves and is golden, stirring frequently to coat nuts. Transfer mixture to prepared baking sheet, and cool completely. Coarsely chop nuts.
Place cream in a bowl. Beat with a mixer at high speed until stiff peaks form. Top each serving with 2 tablespoons whipped cream and about 1 tablespoon nuts.
11 Responses to "Pumpkin Pie Pudding"
That sounds great and I have been dabbling with some lighter recipes lately. I am excited to try this one!
mmm, gingersnaps would be wonderful with this pudding! then again, im always up for gingersnaps! 🙂
Mmmm that pumpkin pie pudding looks sooo delicious! I can hear it calling my name right now, YUM! I love your photos too, so pretty (as always!) 🙂
It's going to be a sad day when all the pumpkin desserts start disappearing.. I love the looks of this one especially!
Oh wow! That looks delish. Crushed gingersnaps definitely. But this looks awesome as is!
Love this dessert!
This pudding looks wonderful! This looks perfect for Thanksgiving coming up before we know it! I love pumpkin too, it's one of the best parts about fall!
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Club Wraps
How to Make It
Step 1
Spread mustard-mayonnaise blend evenly over 1 side of each tortilla, leaving a 1/2-inch border. Layer turkey and next 6 ingredients evenly over tortillas; sprinkle with salt and pepper.
Step 2
Roll up tortillas; cut in half diagonally, and secure with wooden picks.


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TALK OF THE TOWN By Orikinla is About Special People, Places, Events and Things Making News.
Tuesday, November 15, 2016
Ford Super Duty Wins 2017 Motor Trend Truck of the Year Award
See the other winners in the following news release.
MOTOR TREND Announces Its 2017 Motor Trend Awards "Of the Year" Winners
Car of the Year, Truck of the Year, SUV of the Year, and Person of the Year announced during Motor Trend Awards live ceremony and webcast in Los Angeles.
LOS ANGELES, Nov. 15, 2016 /PRNewswire/ -- MOTOR TREND today announced the Motor Trend Awards winners of the Golden Calipers for Car of the Year, Truck of the Year, SUV of the Year, and Person of the Year during a red carpet ceremony. An audience of industry executives and celebrity guests celebrated the winners at the Theatre at Ace Hotel in Downtown Los Angeles. The awards show was streamed live on the Motor Trend OnDemand SVOD service, YouTube, and the MOTOR TREND website. An OnDemand replay is available, which features award content, including complete details on the contenders, finalists, and winners, and a replay of the event broadcast.
"What an exceptional night to honor the best of the best in the industry," says Edward Loh, editor-in-chief of MOTOR TREND. "We are honored to present this year's coveted Car of the Year, Truck of the Year, SUV of the Year, and Person of the Year to some of the most well-deserving and innovative recipients we have had yet."
This year's finalists were evaluated against six key criteria: safety, efficiency, value, advancement in design, engineering excellence, and performance of intended function. Judges for each program came from the MOTOR TREND staff but also included two special guest judges for Car of the Year (legendary car designer Tom Gale and product development guru Chris Theodore) and one special guest judge for SUV of the Year (sales and marketing veteran Mike Accavitti). The Person of the Year was chosen from MOTOR TREND's annual Power List of the automotive industry's 50 most influential people.
The details of the awards are:
2017 MOTOR TREND Car of the Year Winner: 2017 Chevrolet Bolt EV
For only the second time in the awards' seven decades, the sound of electrical energy being converted into motion and the sound of the automotive world shifting on its axis convinced the MOTOR TREND judges to select the Chevrolet Bolt EV as this year's Car of the Year winner.
The Bolt EV was the first battery-powered vehicle to be conceived by GM to be a viable, affordable, mass-market, game-changing electric car, and just two numbers show why. The EPA has certified the Bolt EV will travel 238 miles on a full charge, and it costs only $29,995 after taking into consideration a $7,500 federal tax rebate.
Following a week of testing at the Hyundai-Kia Motors California Proving Ground, the MOTOR TREND judges found, "the most impressive thing about the Bolt EV is that there are no caveats and no 'for an electric car' qualifiers needed in any discussion. It is, simply, a world-class small car, and that's before you factor in the benefits inherent in the smoothness, silence, and instant-on torque provided by the electric motor."
In awarding the Bolt EV its COTY status, Angus MacKenzie, International Bureau Chief for TEN: The Enthusiast Network, calls this year's winner a "roomy, practical, quiet, and comfortable compact hatchback; an energy-efficient small car; and a benchmark electric vehicle—all in one."
2017 MOTOR TREND Truck of the Year Winner: 2017 Ford Super Duty
Out of this year's three impressive finalists tested at Fiat Chrysler Automobiles' Arizona proving ground, the MOTOR TREND judges named the 2017 Ford Super Duty MOTOR TREND's 2017 Truck of the Year winner.
The Ford Super Duty remains cool under extreme pressure, regardless of the circumstances. The design as a whole advances the direction of the previous generation without losing or abandoning its signature look or deviating from the consumer mission. The judges were extremely impressed with the performance of the F-350 dual-rear-wheel diesel as, despite weighing in at 8,643 pounds, it returned an outstanding 16.3/20.5/18.0 mpg city/highway/combined. The Super Duty's ability to extend blind-spot detection to cover a trailer adds an important layer of safety, as does the ability to monitor six trailer tires' pressures and the trailer lights on the dashboard.
"With its latest Super Duty, Ford has set new benchmarks for capability and functionality. We have no doubt the competition will race to meet Ford's new standard," says MOTOR TREND Associate Editor Scott Evans.
2017 MOTOR TREND SUV of the Year Winner: 2017 Mercedes-Benz GLC
Mercedes-Benz SUVs are no strangers to the MOTOR TREND Of the Year awards. This year, the 2017 Mercedes-Benz GLC becomes the fourth Mercedes-Benz SUV to win the Golden Calipers as the MOTOR TREND SUV of the Year winner.
Thorough testing at Honda's recently renovated proving ground near Mojave, California, showed that, despite weighing in at 4,078 pounds, the GLC300 gets to 60 mph in a respectable 6.8 seconds and runs down the quarter-mile in 15.3 seconds at 89.7 mph. In addition, the C-Class interior is the best in its class, as the seats are sofa-soft yet still supportive. Its luxury is highlighted with fine leather and wood details. According to the judges, this is the first time a luxury SUV has been as good as or better than the equivalent price-category sedan it's based on.
Guest judge Mike Accavitti says, "Overall, this is a great vehicle. You know you're getting into a Mercedes as soon as you open the door to the GLC. The quality of the materials and the elegance of the design are very consistent with the Mercedes-Benz brand proposition and reputation."
2017 MOTOR TREND Person of the Year Winner: Elon Musk, CEO Tesla Motors
There is no other company or CEO generating more interest in the industry today than this year's 2017 MOTOR TREND Person of the Year. Jumping from last year's number six spot to number one for 2017, MOTOR TREND is honored to recognize Elon Musk, CEO of Tesla Motors.
Not only is he CEO of the leading electric-vehicle company, Musk also leads companies that launch rockets into space and attempt to convert America's key energy source to solar. Musk continues to lure in tens of thousands of loyal followers willing to buy his products from the future.
Visit MOTOR TREND's media asset site athttp://press.motortrend.comfor downloadable PR materials including press release, logos, B-roll video, and photos for Car, Truck, SUV, and Person Of the Year awards.
About MOTOR TREND
MOTOR TREND, a media brand of TEN: The Enthusiast Network, was founded in 1949 and is internationally recognized as one of the leading names in the automotive category. The MOTOR TREND brand is composed of Motor Trend magazine; the award-winning website MotorTrend.com; Motor Trend OnDemand subscription video-on-demand service, Motor Trend Auto Shows; Motor Trend Audio; Motor Trend en Español; Motor Trend India; and the renowned Motor Trend Car of the Year, SUV of the Year, Truck of the Year, Person of the Year, and Best Driver's Car awards programs.
About TEN: The Enthusiast Network
TEN: The Enthusiast Network is the world's premier transmedia network of enthusiast brands, such as MOTOR TREND, AUTOMOBILE, HOT ROD, SURFER, TRANSWORLD SKATEBOARDING, and GRINDTV. With more than 60 websites, 50 publications, 50 annual events, the Motor Trend OnDemand subscription video-on-demand service, as well as the world's largest automotive and action/adventure sports media platforms, TEN inspires enthusiasts to pursue their passions. For more information, visitenthusiastnetwork.com.
CONTACT: Rob Quigley, Senior PR and Social Media Manager, Marketing, TEN: The Enthusiast Network,email@example.com 310-363-4086
Photo -http://photos.prnewswire.com/prnh/20161114/439350
Photo -http://photos.prnewswire.com/prnh/20161114/439351
Photo -http://photos.prnewswire.com/prnh/20161114/439352
Photo -http://photos.prnewswire.com/prnh/20161114/439353
Logo -http://photos.prnewswire.com/prnh/20150817/258789LOGO
SOURCE TEN: The Enthusiast Network
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35 Y. Gianchandani, K. Takahata, "Design and Fabrication of Stents Using Planar Metal Foils," U.S. Patent 9,440,302; issued September 13, 2016 (UM) 34 X. Fan, Y. Gianchandani, J. Liu, "Adaptive Micro-Gas Chromatography," U.S. Patent No. 9,341,604;' issued May 17, 2016 (UM) 33 Y. Gianchandani, R. Gharpurey, C. Eun, "Wireless Sensing and Communication Utilizing RF Transmission from Microdischarges," U.S. Patent No. 9,083,392 B2; issued July 14, 2015 (UM) 32 S. Chiravuri, A. T. Evans, Y. Gianchandani, J. M. Park, "Dual Drug Delivery Device," U.S. Patent No. 8,945,052; issued Feb. 6, 2015 (UM) 31 Y. Gianchandani, S. Wright, "Microdischarge-Based Pressure Sensor and Method," U.S. Patent No. 8,638,106; issued Jan 28, 2014 (UM) 30 Y. Gianchandani, T. Li, R.Y. Gianchandani, "In-Situ Tissue Analysis Device and Method," U.S. Patent No. 8,467,867; issued June 18, 2013 (UM) 29 S. Chiravuri, A. T. Evans, Y. Gianchandani, J. M. Park, "Dual Drug Delivery Device," U.S. Patent No. 8,323,246; issued Dec. 4, 2012 (UM) 28 Y. Gianchandani, N.K. Gupta, "The Use of a Zeolite Material Within the Flow Channel of a Gas Pump Based on Thermal Transpiration," U.S. Patent No. 8,235,675; issued August 7, 2012 (UM) 27 S. Green, Y. Gianchandani, M. Richardson, "Wireless Biliary Stent System with Wishbone-Array Resonant Magnetoelastic Sensor and Conformal Magnetic Layer," U.S. Patent No. 8,212,552; issued July 3, 2012 (UM) 26 A. Gaitas, Y. Gianchandani, "A Hybrid Contact Mode Scanning Cantilever System," U.S. Patent No. 8,156,568; issued April 10, 2012 (Picocal) 25 Y. Gianchandani, T. Li, R.Y. Gianchandani, "Micromachined Tissue-Contrast Sensor and Method for Integrating Sensors in Biopsy Tools," U.S. Patent No. 7,927,288 B2; issued April 19, 2011 (UM) 24 Y. Gianchandani, K. Takahata, "Electromagnetic Flow Sensor Device," U.S. Patent No. 7,922,667; issued April 12, 2011 (UM) 23 Y. Gianchandani, G. F. Nellis, S. A. Klein, J. M. Park, A. T. Evans, R. Taylor, T. Brosten, "Low-Power Piezoelectric Micro-Machined Valve," U.S. Patent No. 7,789,371; Issued September 7, 2010 (WARF/UM) 22 21 Y. Gianchandani, K. Takahata, K.D. Wise, A. DeHennis, "Antenna Stent Device for Wireless, Intraluminal Monitoring," U.S. Patenet 7,452,334; issued November 18, 2008 (UM) 20 Y. Gianchandani, S. McNamara, "Packaged Micromachined Device Such as a Vacuum Micropump, Device Having a Micromachined Sealed Electrical Interconnect and Device Having a Suspended Micromachined Bonding Pad," U.S. Patent 7,367,781; issued May 6, 2008 (UM) 19 Y. Gianchandani, A.S. Basu, "Liquid Flow Actuation and Suspension Manipulation Using Surface Tension Gradients," U.S. Patent No. 7,358,051; issued April 15, 2008 (UM) 18 S. McNamara, Y. Gianchandani, "Systems and Methods for Thin Film Thermal Diagnostics with Scanning Thermal Microstructures," U.S. Patent No. 7,262,066; issued Aug. 28, 2007 (Picocal) 17 Y. Gianchandani, C. Wilson,U.S. Patent No. 7,157,718; issued Jan. 2, 2007 (UM) 16 Y. Gianchandani, C. Wilson, L. Que, B. Mitra, P. Selvaganapathy,U.S. Patent No. 7,142,303; issued Nov. 28, 2006 (UM) 15 Y. Gianchandani, L. Chu, K. Takahata, P. Selvaganapathy, J.L. Shohet,U.S. Patent No. 7,116,115; issued October 3, 2006 (UM) 14 Y.B. Gianchandani, S.P. McNamara, J. Lee, A. Basu,U.S. Patent No. 7,073,938; issued July 11, 2006 (UM) 13 Y. Gianchandani, M.-H. Li, J. Wu, "Micromachined Scanning Thermal Probe Method and Apparatus," U.S. Patent No. 6,692,145; issued Feb. 17, 2004 (WARF) 12 Y. Gianchandani, C. Wilson, "Method and Apparatus for Glow Discharges with Liquid Microelectrodes," U.S. Patent No. 6,686,998; issued February 3, 2004 (WARF) 11 Y. Gianchandani, K. Takahata, "Micro-Electro-Discharge Machining Utilizing Semiconductor Electrodes," U.S. Patent No. 6,586,699; issued July 1, 2003 (WARF) 10 Y. Gianchandani, S. McNamara, "Micromachined Shock Sensor," U.S. Patent No. 6,619,123; issued Sept. 16, 2003 (WARF) 9 J. Hetrick, Y. Gianchandani, L. Chu, "Micromechanical Electrothermal Actuation Apparatus," (Displacement Amplifier) U.S. Patent No. 6,594,994 B1; issued July 2, 2003 (WARF) 8 Y. Gianchandani, K. Takahata, "Micro-Electro Discharge Machining Method and Apparatus," U.S. Patent No. 6,624,377 B2; issued September 23, 2003 (WARF) 7 J. Booske, K. Thompson, R. Cooper, Y. Gianchandani, "Method of Bonding a Stack of Layers by Electromagnetic Induction Heating," U.S. Patent No. 6,951,798; issued Oct. 4, 2005 (WARF) 6 K. Fischer, H. Guckel, Y. Gianchandani, "Bi-Directional Micromechanical Latching Linear Actuator," U.S. Patent No. 6,607,305; issued Aug. 19, 2003 (WARF) 5 Y. Gianchandani, C. Wilson, "Method and Apparatus for Etching and Deposition using Micro-Plasmas," U.S. Patent No. 6,827,870; issued Dec. 12, 2004 (WARF) 4 L. Que, G. Witjaksono, Y. Gianchandani, "Micromechanical Phase-Shifting Gate Optical Modulator," U.S. Patent No. 6,377,718 B1; issued Apr. 23, 2002 (WARF) 3 Y. Gianchandani, "Sealed Capacitive Pressure Sensors," U.S. Patent No. 6,470,754 B1; issued Oct. 29, 2002 (WARF) 2 Y. Gianchandani, "Method of Forming Micromachined Sealed Capacitive Pressure Sensors," U.S. Patent No. 6,460,234 B1; issued Oct. 8, 2002 (WARF) 1 Y. Gianchandani, "Micromachined Strain Sensor with Differential Capacitive Readout," U.S. Patent No. 6,609,913 B1; issued Aug. 19, 2003 (WARF)
14 Y. Qin, Y. Gianchandani, "Progressive Cellular Architecture for Microfabricated Gas Chromatograph," patent pending (UM) 13 D. Sun, Y. Gianchandani, T. Li, J. Liao, "Wireless Gastric-Intestinal Sampling Device for Diagnosis of Gastric-Intestinal Diseases and Optimization of Drug Development," patent pending (UM) 12 J. Stein, Y. Gianchandani, V. Pepakayala, "Magnetoelastic actuator for glaucoma drainage devices (MA-GDD)," patent pending (UM) 11 T. Li, Y. Gianchandani, Y. Sui, R. Meredith, "Environmental Logging Microsystem (ELM)," patent pending (UM) 10 Y. Gianchandani, S. An, Y. Qin, "Silicon Micromachined High Flow Gas Pump," patent pending (UM) 9 Y. Gianchandani, S. Green, K. Sarabandi, M. Kanj, H. Schmidt, J. Tang, J. Wu, "Interrogating Subterranean Hydraulic Fractures Using Magnetoelastic Resonators and Interrogating Antenna Arrays," patent pending (UM) 8 Y. Gianchandani, J. Tang, S. Green, "Frame-Suspended Magnetoelastic Resonators," patent pending (UM) 7 Y. Gianchandani, T. Li, Y. Ma, "Packaged Microsystems," patent pending (UM) 6 Y. Gianchandani, V. Pepakayala, S. Green, "Passive Wireless Strain Sensor," patent pending (UM) 5 Y. Gianchandani, C. Eun, X. Luo, M. Kushner, Z. Xiong, J.-C. Wang, "Multi-electrode pressure sensor concept and method of fabrication," patent pending (UM) 4 Y. Gianchandani, Y. Qin, "Standardized, Scalable, Micro-Gas Chromatograph," patent pending (UM) 3 Y. Gianchandani, K. Visvanathan, "Cauterization Needle with Embedded Sensing," patent pending (UM) 2 William (Rick) F. Weitzel, Y. Gianchandani, "Methods and Systems for Determining Blood Flow Volume in a Blood or Fluid Conduit, Motion, and Mechanical Properties of Structures Within the Body," patent pending (UM) 1 A. Galvanauskas, Y. Gianchandani, K.-H. Liao, K. Udeshi, L. Que, "A Micromachined Device for Refractive Index Modulation in Optical Fibers and Arbitrary Shaping of Optical Waveforms," patent pending (UM)


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The great white shark (scientific name: Carcharodon carcharias) is not the biggest shark (that title goes to the whale shark), but they are the largest predatory fish on Earth. According to the Guinness World Records Book, full grown adults are average 4.3–4.6 m (14–15 ft) in length, and generally weigh 520–770 kg (1,150-1,700 lb). But there are many claims of huge specimens up to 10 m (33 ft) in length. Newspapers and home photo albums are full of unconfirmed huge great white tales. And although few have been properly authenticated, there are a lot of circumstantial evidence to suggest that some great whites grow to more than 6 m (20 ft) in length.
It is really difficult to measure that how large a shark actually is. The reason is simple: they live in water, and it is not entirely safe to get close to them. Safety is one thing, the other thing is their incredible speed: great white sharks can accelerate to over 56 km/h (35 mph).
Another difficulty is, their bodies are comprised of mostly water too, so when they are landed the water dries up, and they become smaller.
In overall, the great white is the fifth largest living fish on earth.
Historically, a number of very large great white shark specimens have been recorded. For decades, many sources including the Guinness Book of World Records, listed two great white sharks as the largest individuals: In the 1870s, a 10.9 m (36 ft) great white captured in southern Australian waters, near Port Fairy, and an 11.3 m (37 ft) shark trapped in a herring weir in New Brunswick, Canada, in the 1930s. Some researchers question these measurements' reliability, noting they were much larger than any other accurately reported sighting. This New Brunswick shark may have been a misidentified basking shark, as the two have similar body shapes. The basking shark (Cetorhinus maximus) is the second largest living fish, after the whale shark, and one of three plankton-eating sharks besides the whale shark and megamouth shark.
The question of the Port Fairy shark was settled in the 1970s when J. E. Randall examined the shark's jaws and "found that the Port Fairy shark was of the order of 5 m (17 ft) in length and suggested that a mistake had been made in the original record, in 1870, of the shark's length".
Another Great White caught off the coast of Malta in 1987 was said to measure in at 7 meters (23 feet). Further studies, however, indicate that that measurement was exaggerated.
So, what is the largest great white shark ever recorded?
There is no clear winner, but there are a few candidates:
The Cuba Shark (1945)
A very large specimen was caught off of the coast of Cuba in 1945. Known as the "Cojimar Specimen", it allegedly weighed 7,000 pounds (3,175 kg) and was 21 feet (6.4 m) in length. It is often cited as the largest great white shark ever recorded. At the time, an entire village seemed to come out for the photo. Several adults stood at the background, while kids sat on the long-dead shark, legs dangling over the side.
Later analysis of the photo by experts, such as R. Aidan Martin of the ReefQuest Center for Shark Research, suggests the shark fell short of its stated size. Martin instead concluded it measured around 16 feet (4.9 m) in length, with a weight that's hard to determine just based on a single photo.
The Seven Star Lake Shark (1997)
A huge great white shark caught in a set-net in Seven Star Lake (Qixingtan), Hualien County, Taiwan, on May 14, 1997. Gross weight of this animal was 2500 kilograms (5,500 pounds) and total length is estimated at 6.7 to 7.0 meters (~22 feet). It is considered as possibly the largest great white shark ever recorded.
The great white shark caught by Vic Hislop in 1985
In the photograph above, we see a huge 21′ 8″ (6.6 meter) great white shark caught by the Australian shark hunter Vic Hislop in 1985. This may be the biggest white shark ever caught. Hislop also believes there are many even bigger sharks out there in our oceans. He also claims to have a caught a bigger one than the one pictured, but couldn't land it.
Contrary to the current belief that the great whites are not natural man-eaters, Hislop believes that the great white sharks can develop a taste for humans, and that once one does, it will travel from beach to beach devouring humans whenever it feels hungry. He says "At least a hundred swimmers disappear every year here and their bodies are never found. Many have been eaten. I've often caught sharks and removed human hands and feet from their stomachs. I even found a human foot still in its sandal." You can read more about this on the Edit International site.
1988 Canada Shark
According to the Canadian Shark Research Center, the world's largest accurately measured great white was 20 feet (6.1 meter) in length. This was a female caught in 1988 at Canada's Prince Edward Island. It is caught by the local fisherman David McKendrick. The shark became tangled in McKendrick's net as he fished off the western side of the island, and died before it was brought to the surface. A large female, the shark was a rarity in the northern seas.
Deep Blue
This enormous shark named "Deep Blue" was spotted near Isla Guadalupe, off the coast of Mexico and is probably the largest great white shark ever to be filmed and believed to be one of the largest great white sharks ever seen. The massive predator was first featured in August by the Discovery Channel in a documentary when researchers tagged the gigantic fish. Researchers believed Deep Blue was pregnant. The shark thought to be around 50 years old and estimated at 20 feet (6.1 meters).
In the video below, a fearless diver high-fiving Deep Blue.
The Marino Bay (Australia) Shark (2016)
An Australian crew has photographed what may be the largest great white shark ever seen, at an approximate length of 23 feet (7 meters). The shark was spotted just 300 feet off the shore of Marino Bay, South Australia. The photo was published on Shark Alerts South Australia facebook page. According to the non-profit organization, "the crew (of the shark patrol helicopter) used their Jet Boat to compare the size which is around 6 meters and the shark was bigger".
But naturally many people are skeptical about the claim. Colin Simpfendorfer, a marine sciences professor at James Cook University, said that: "The size issue from photos like this is always challenging. You can get a sense of its size, but measuring it to that sort of accuracy is always a challenge, particularly when there's very little in the way of size reference in the picture."
In a comment on their facebook page, Shark Alerts South Australia says: "These guys are professionals so I can ensure you no lies on the length here… As stated the "biggest they've ever seen".
Relationship with humans
The great white sharks also known as the great white, white pointer, white shark, or white death. Despite the great white shark is responsible for by far the largest number of recorded shark attacks on humans, many scientists believe that they do not prey on humans. In the Mediterranean Sea there have been 31 confirmed attacks against humans in the last two centuries, most of which were non-fatal. Scientists say many of the attacks are "test bites", and the fatalities are usually caused by blood loss from the initial bite rather than from critical organ loss or from whole consumption.
Humans are not appropriate prey because the shark's digestion is too slow to cope with a human's high ratio of bone to muscle and fat. Accordingly, in most recorded attacks, great whites broke off contact after the first bite. However, some researchers have hypothesized that the reason the proportion of fatalities is low is not because sharks do not like human flesh, but because humans are often able to escape after the first bite. In the 1980s, John McCosker, Chair of Aquatic Biology at the California Academy of Sciences, noted that divers who dove solo and were attacked by great whites were generally at least partially consumed, while divers who followed the buddy system were generally rescued by their buddy. McCosker and Timothy C. Tricas, an author and professor at the University of Hawaii, suggest that a standard pattern for great whites is to make an initial devastating attack and then wait for the prey to weaken before consuming the wounded animal. Humans' ability to move out of reach with the help of others, thus foiling the attack, is unusual for a great white's prey.
- Great white shark on wikipedia
- Largest Great White Shark on Discovery.com
- Largest Predatory Fish on Guinness World Records Book
- What are the Biggest Great White Sharks Ever Recorded? on SharkFacts


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GREENVILLE, S.C. - King College's Mark Dockery played his way to the NCCAA Division I All-American First Team, as announced by the national office.
Dockery, a senior forward from Nicklesville, Va., was one of 10 players on the first team. He finished the year with a 20.1 points per game scoring average thanks to a school record 141 three-pointers. Dockery started all of King's 34 games on the season as he added a .849 free throw percentage.
He posted single-season program records for points (684), field goals attempted (481), and three-point field goals (141). Dockery also added the King career records for scoring (1,826), three-point field goals (388), three-point field goals attempted (978) and steals (164).
Of the 34 games he scored 20 or more 21 times including a career-best 40 points against Life (Ga.) University which featured a school-record 21 free throws made.
Dockery was a NCCAA All-Mid-East Region first team player selection.
King finished the season 19-15 with a third-place finish at the NCCAA Division I National Tournament after winning the Mid-East Region Tournament.
To see the NCCAA All-American team, click here.


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The United States signaled Monday it is ready for extended negotiations in Beijing aimed at an accord ending North Korea's nuclear program. The chief U.S. delegate to the talks, Assistant Secretary of State for East Asian Affairs Christopher Hill, met his North Korean counterpart on the eve of Tuesday's opening of a new round of the six-party talks.
The first three rounds of the six-party talks lasted only a few days each, with little give-and-take among the parties.
But officials here say the new round could be different, with the United States expecting a formal North Korean response to the proposal it made a year ago, and setting no deadline for ending the discussions.
A senior State Department official who spoke to reporters on terms of anonymity said the U.S. team is prepared to remain in Beijing "for some period of time," and open to a format that could include breaks to allow delegations to report home and seek instructions from their governments.
In the previous round of six-party talks in Beijing in June of last year, the United States said it was prepared to be part of multi-lateral guarantees for North Korea's security under an accord bringing a permanent and verifiable end to its nuclear weapons program.
U.S. officials said other parties to the talks could provide North Korea with aid as the disarmament process unfolded, and they have left open the prospect of increased U.S. diplomatic recognition and aid for Pyongyang once it was completed.
At a news briefing, State Department Spokesman Sean McCormack declined to address a report by Japan's Kyodo news agency that the United States could be ready to set up a diplomatic liaison office in Pyongyang if North Korea abandoned its nuclear program.
But he did say North Korea would enjoy a better relationship with all the parties to the talks, if it was ready to bargain in good faith and make the strategic choice to abandon its pursuit of nuclear arms.
"As the Secretary (Rice) has said, North Korea needs to make a strategic decision to give up its nuclear program," Mr. McCormack says. "And if it does make that strategic decision and move forward, it can realize a different kind of relationship with the other members of the six-party talks. And the core idea behind the June, 2004 (U.S.) proposal is that good faith acts on the part of North Korea would be met in turn by good-faith actions by the other members of the six-party talks."
Spokesman McCormack said Assistant Secretary Hill's 75-minute meeting Monday with North Korean Vice Foreign Minister Kim Kye-gwan was businesslike, and an opportunity to "compare notes," but not a negotiation.
U.S. delegates had met separately with North Koreans during previous rounds, but Monday's meeting was the first that preceded the start of a session of talks.
The senior official who spoke here said U.S. officials have been advised by China to expect a formal reply to the American proposal from North Korea, which has limited its reaction thus far to critical comments in its official media.
He also said North Korea, like other participants in the talks, is free to raise issues or concerns not covered by the U.S. proposal.
Pyongyang agreed to return to the talks July 9th during Secretary of State Condoleezza Rice's visit to Beijing, and after South Korea proposed to meet all North Korea's electricity needs in exchange for nuclear disarmament.
In addition to the United States, China and North Korea, the six-party talks also include South Korea, Japan and Russia.


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This past Thursday a new bill was passed that would effectively end the prohibition on the use of medicinal cannabis. While it was certainly a happy occasion to note the bipartisan effort put in, it is also frustrating to most to still have the struggle behind legalization. To have the amount of pushback against legislation in favor of a plant that has the ability to help many, is asinine to the majority of the public's opinion.
Many beg the question, why do we need permission to use treatment that works the best for various illnesses? It seems to be a clear violation of the laws and rights surrounding personal sovereignty, but that ceases to bother Attorney General Jeff Sessions who essentially asked congress for the permission to prosecute those involved with medicinal cannabis.
Jeff Sessions is notably in disbelief of cannabis as a medicine and continuously disregards patients stories of how the wonder-drug has helped them.
A woman named Charlotte Figi was diagnosed with a severe case of epilepsy at an early age. By the age of three, Figi was having around three-hundred seizures per week. A miserable existence for such a young girl. All of the conventional forms of treatment failed to work.
Charlottes parents were desperate for relief for their child and had heard of another child with a similar medical diagnosis using medicinal cannabis to cure his condition.
As soon as they heard, they got ahold of the medicine and began giving it to Charlotte. Almost instantly her symptoms improved. Today, Charlotte has very few seizures all thanks to the help of medicinal cannabis. Those who developed the specific strain of cannabis with little to no incidence of psycho activity in the drug, appropriately named their strain, Charlotte's web. Today that strain has helped many children to treat their conditions without the worry of getting high.
Aside from this, there has been several instances of medical cannabis improving the lives of people wit conditions across the board.
So why invest in cannabis? As a direct result of our capitalist agenda, the freedom to impart positive change through a free market without the threat of violence is one of the most powerful ways to start a movement. Because of this, the dangers involved in investing in cannabis stay at a constant level.
In addition to its safety, the main attraction is that investing in marijuana is incredibly profitable. As a new industry on the rise, the potential for monetary gain is as high as ever.
Last year, sales from cannabis hit over a staggering twenty billion dollars, with an annual growth rate of twenty-five percent. This is expected to only get higher and is surpassing the growth rate of the famed dot-com era.
The bottom line lies in the fact that when an industry has this much potential it is difficult for it to lean towards a downtrend at any time. This would be especially difficult for someone like Attorney General Jeff Sessions to shut down.
Because of this and many other reasons, medicinal cannabis remains one of the highest rated, highest increasing and admittedly the most moral investment that one can make.


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cafe Fåtöljen
recommendation by takemesomewhere
It's one of those nice european cozy cafes to take a rest from the whole day of walking down the streets of Stockholm or a cool place to meet some friends and have a coffee!There you can try one of the best pies, cheesecakes and enjoy traditional swedish baking.If you get hungry - they even have sandwiches and sallads and prices are fair enough:)The armoshpere is kind of underground and cozy at the same time.You feel yourself very rock'n'roll when you see a giant picture of Jagger on the wall!
Phone number: Tel. 08 - 669 63 54 or 08 - 644 06 05


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- Home
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- Pin the Mask On the SuperGirl Printable Party Game - Printable PDF - Instant Download
Product Description
Pin the Mask on the Supergirl Printable Party Game. A fun addition to your party - just print & play! You get all of the hair colors shown!
>This is a digital file. You will receive no printed product.
>You can print the Game Poster at a copy centre or photo lab. This file has the wording "pin the mask on the hero" (see pic 1). The following sizes are included in your downloads: 11x17, 18x24, 20x30.
>The Game Mask Pieces are in letter size (8.5x11) for convenient last minute printing (at home if necessary).
>For the Game Mask Pieces, you can either print the "Ready to Print" JPEG file & write in the players' names by hand OR use the Editable Text PDF file of the Game Mask Pieces in Adobe Reader to type in the players' names.
>The Editable Text PDF files can be used with Adobe Reader only. You simply open the files in Adobe Reader and type over my sample text. Instructions are included. You can download Adobe Reader easily and for free at www.get.adobe.com/reader.
>The Editable Text PDF files must be used on a desktop or laptop. The editable text files will not work on a smartphone or tablet.
>The Editable Text PDF files can only be printed at home using Adobe Reader or at a location that can print password protected PDF files (e.g. Office Depot).
>Game Mask Pieces are set up: 11x17 - 4 per letter size page, 18x24 - 4 per letter size page, 20x30 - 3 per letter size page.
-latest version of Adobe Reader for PDF files available for free download at www.get.adobe.com/reader if you want to use the Editable Text PDF files
-Printer (or have printed at your local office store or printer)
-Ink for your printer (if printing yourself)
-Paper (if printing at home)
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Max and Miles are back in the game! Pacman!!!
The first weekend was a raging success. Everyone wanted to be in a good mood and the weather was on our side. Murphy's Law stipulates that the next few weeks will bring us totally crappy weather (it's the ice cream equivalent of Groundhog Day). If so, don't be surprised if we close up shop for the day. You probably wouldn't even notice because who goes out for ice cream in crappy weather?!?
Thanks to everyone who brought us a great weekend!!!


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The foundation of Dollar Rent A Car is built on a philosophy of exceptional customer service. That fundamental principle is passed on to each employee through our unique Customer Driven training program.Our attention to customer service and our fleet of fine quality rental cars and car hire products, is complemented by our strong line-up of business travel and vacation planning services...
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This is a franchise location and NOT owned by the corporate. Which means the owner has free
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experiance- Never Rent from this location.
Competitive rental values offered on 11 classes of airbag-equipped vehicles including Chrysler, Dodge and Jeep models.
Do NOT rent from here. I rented a car here with full insurance and returned it on the day agreed upon. I received a call a couple days later that they could not find my keys to which I told them...
This location is very convenient for me as I live in Brooklyn, NY and it only takes me 45 minutes to catch the F train to the PATH train to Newport. I rent from here a couple of times every year,...
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The Extras: Frequent renters can save time with Dollar's free Fastlane program which provides expedited counter service and more.


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Saturday August 5, 2006
Python vs. Perl vs. C++
Last month I described a program I wrote for a machine translation project in Perl and how it turned out to be much slower than I expected. As you may recall, I rewrote the program in C++, and it was a hundred times faster. I suspected this was due to all the conversion in Perl back and forth from strings to floating point numbers in the program, and to all the string copying necessary for function calls. Some people (in person and in the comments) suggested I should try rewriting it in Python, which has native floating point numbers, to see if it was any faster.
It wasn't. I'd never written a Python program before, so I timed myself as I ported and debugged it—about an hour and a half. When I finally had it working, it ran about as slow as the Perl version. A full run of the Perl version takes 20 hours and I wasn't feeling patient enough to let the Python version run to completion, but eyeballing the program's progress indicator showed the Perl and Python versions were about the same speed, while the C++ version was much faster.
This implies it's not actually all the string conversion and copying that are making the program slow, because Python doesn't do those. So what's slowing Perl and Python down? I decided to find out. I wrote little programs called add, mult, and func, in C++, Python, and Perl—nine programs altogether. Each consists of a single loop, and the names tell you what happens in that loop: add adds integers, mult multiplies floats, and func calls a dummy function. (In fact, mult and func also do an integer add for the loop counter, so they're really like add plus an additional operation.) All of them take a single command-line argument which tells them how many times to loop.
I started running them, increasing the number of iterations by a factor of ten each time, until I got some nice, macroscopic timings that were big enough to swamp any fixed startup cost. The magic number was 10,000,000 iterations. I've collated the timings, which are the "real" times reported by the Unix time command, in the table below. The "Slowdown" column tells how many times slower than the fastest (C++) version each program is:
Program Language time (ms) Slowdown add C++ 23 add Perl 1464 64 x add Python 3242 141 x mult C++ 99 mult Perl 2686 27 x mult Python 5285 53 x func C++ 43 func Perl 5143 120 x func Python 6413 149 x
As you can see, it's not specifically the floating point operations or the function calls that are causing the trouble. Even a tight loop containing nothing but integer operations is 64 times slower (Perl) or 141 times slower (Python) than the C++ version. Doing floating point multiplications or function calls in the loop affects the timings a bit, but the results are still roughly proportional: C++ is fast, Perl is an order of magnitude or two slower, and Python is roughly another factor of two slower than that.
This leads me to think that the performance differences are due almost entirely to the fact that Python and Perl are interpreted languages. I guess there's a lot of overhead associated with compiling the code (or the bytecode, in the case of Python) repeatedly as it's executed. At least, I'm pretty sure that's what's going on in the interpreters—if anyone knows better, I'd be curious to hear about it.
These results are pretty disappointing. I like the high-level scripting languages, with all their built-in convenience, for doing quick-and-dirty programming. As I said, this was my introduction to Python, which I'm about to use for an unrelated project, and it's a pretty nice language—very terse, kind of like pseudo-code that actually runs. Unfortunately, for any project that's going to be computationally intensive—which is pretty much the definition of "computational linguistics"—a 25-to-150-times performance hit just isn't acceptable. With Python (and maybe Perl, I'm not sure) it's possible to write the innermost loops in C or C++, but I don't really like that solution for two reasons. First, as long as I'm going to have to write some C++ for speed, I might as well write it all in C++ and have the whole program be fast. Second, if I ever distribute the code, it narrows the potential audience if they have to know, and have installed, two computer languages to use it instead of just one.
Hmm, now I'm wondering how Java would perform. No! Must... resist! Must... finish... generals paper...
[Note: This is actually the third version of this post. The numbers reported in the original version were wrong—even though I'd called g++ with the -O0 option, it still did some optimizations that threw the timings off, especially for mult. After this was pointed out in the comments, I tried to do a quick fix and ended up screwing it up much worse. Oops.
In particular, multiplying by -1.0 was being compiled into an exclusive-or instruction instead of a floating point multiplication, so it ran too fast. My quick fix was to multiply by -1.1 instead, but raising -1.1 to the ten millionth power overflowed repeatedly and wasted a bunch of time in floating point exception handling. That made it run way too slow. The real fix was to multiply twice in each loop, once by 10.0 and once by 0.1 (and do the loop half as many times). That correctly compiles to floating point multiplication instructions and never overflows. I also had to make all the other programs increment their loop counters by two in order to get an addition instruction instead of a special-purpose increment instruction, but the performance difference there was very small.
I decided that having an update and an update to that update in this post would be hopelessly confusing, so I rewrote the whole thing instead. Thanks to Joshua "Necro" Macy, Russell "Mimsy was the" Borogove, and the myserious KK for pointing this stuff out and keeping me honest. I've left all the original comments intact, so if you're interested, you can probably reconstruct most of the sordid history of this post.
Oh, and greetings to any future hiring committes who might be reading this. Now, you might be thinking that the initial errors in this post imply a certain sloppiness on my part, but I prefer to focus on how the final, corrected version demonstrates my committment to getting the details right...eventually.]
[Update: In response to several requests, here's the source for the various programs:
#include <stdlib.h>
int main(int argc, char** argv)
int i = 0;
int count = 2 * atoi(argv[1]);
while (i < count) {
i += 2;
return 0;
$i = 0;
$count = 2 * $ARGV[0];
while ($i < $count) {
$i += 2;
import sys
i = 0
count = 2 * int(sys.argv[1])
while i < count:
i += 2
#include <stdlib.h>
int main(int argc, char** argv)
double val = 1.0;
int i = 0;
int count = 2 * atoi(argv[1]);
while (i < count) {
val *= 10.0;
i += 2;
val *= 0.1;
i += 2;
return 0;
$val = 1.0;
$i = 0;
$count = 2 * $ARGV[0];
while ($i < $count) {
$val *= 10.0;
$i += 2;
$val *= 0.1;
$i += 2;
import sys
val = 1.0
i = 0
count = 2 * int(sys.argv[1])
while i < count:
val *= 10.0
i += 2
val *= 0.1
i += 2
#include <stdlib.h>
void func(void)
int main(int argc, char** argv)
int i = 0;
int count = 2 * atoi(argv[1]);
while (i < count) {
i += 2;
return 0;
sub func
$i = 0;
$count = 2 * $ARGV[0];
while ($i < $count) {
$i += 2;
import sys
def func():
i = 0
count = 2 * int(sys.argv[1])
while i < count:
i += 2
If you have different results on your system, feel free to post the results in the comments.]
[Update: For some reason, this post seems to be accepting new comments but not displaying them. I'm hoping that this update mysteriously causes the post to republish correctly. (Get in the car and try it again!) If not, my apologies to John-Mark Gurney and Andrew.]
I am The Tensor, and I approve this post.
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Python compiler package would be the place to go for bytecode compilation.
Posted by: Carson at Aug 4, 2006 6:50:36 AM
That shouldn't be necessary, though. Python always compiles to bytecode, and even saves the results so it doesn't have to recompile unless the source code has changed (unless you don't have permissions to create the equivalent .pyc files on disk). There's something else going on here, I think, maybe having to do with object creation and deletion?
If you're actually interested in pursuing this (perhaps for future Python projects), I'd post a question and maybe some sample code showing the loop to comp.lang.python.
Posted by: Joshua Macy at Aug 4, 2006 8:59:42 AM
My understanding is that Perl is compiled at startup, also, though I'm prepared to be completely wrong on this.
Perl's scalar datatype is, most fundamentally, a string, and it has to convert to and from numeric types every time it does a math operation. I'm guessing that's the real killer for you.
You can check out the "math" modules in CPAN; depending on what exactly you're trying to do, you might find a package that helps.
Posted by: Russell Borogove at Aug 4, 2006 10:46:38 AM
Python always compiles to bytecode, and even saves the results so it doesn't have to recompile unless the source code has changed (unless you don't have permissions to create the equivalent .pyc files on disk).
You know, I read that—that Python always compiles to bytecode and saves it in a .pyc file—but I never saw it happen, and I do have permission to write to the directory I was running from. The code is in a .py file with #!/usr/bin/python as the first line. When I run it, should that produce a .pyc file?
Posted by: The Tensor at Aug 4, 2006 1:19:42 PM
Uh, what sort of optimization-flags did you use for C++? Have you disassembled the source-code to make sure the entire program haven't been optimized away? With such a simple program (unless each number added/multplied etc. was random), it is entirely possible that C++ simply did all the computations at compile-time, leaving a binary that just prints out the answer... (It happened to me when doing similar comparisons.) Disassemble and look for JMP, JMZ etc or similarly appropriate for your architecture.
Posted by: KK at Aug 4, 2006 1:54:20 PM
I ran g++ with -O0 to turn off all the optimizations.
Posted by: The Tensor at Aug 4, 2006 2:24:02 PM
Ah, according to this Python doesn't create the .pyc files if you run a script by giving its name on the command line (i.e. if you're taking advantage of the #! magic instead of running python script-name). I hadn't run into that before, 'cause I tend not to use the #! construct except for cgi... The .pyc files only speed up the load, though, not the running (by saving the initial parse to bytecode), so that can't be the source of the slowness you're seeing. That is to say that whether or not Python saves the result, what it's actually operating on internally is the bytecode that it created out of your source (this is basically the same thing that java does, with its jvm). There is a sort of JIT compiler for Python, to render the bytecode all the way down to machinecode, called Psyco that can sometimes produce some amazing speed-ups...
Posted by: Joshua Macy at Aug 4, 2006 2:50:44 PM
Whoa! What platform are you on that a floating point multiply in C++ is 100 times slower than XOR?
Posted by: Russell Borogove at Aug 4, 2006 4:50:27 PM
What platform are you on that a floating point multiply in C++ is 100 times slower than XOR?
arch says i686.
100 does seem high, but I don't see any crazy discrepancies in the code. Here are the innermost loops of both programs:
.L2: movl -4(%ebp), %eax cmpl -8(%ebp), %eax jl .L4 jmp .L3 .L4: leal -4(%ebp), %eax addl $2, (%eax) jmp .L2 .L3: movl $0, %eax leave ret
.L2: movl -12(%ebp), %eax cmpl -16(%ebp), %eax jl .L4 jmp .L3 .L4: fldl -8(%ebp) fldl .LC1 fmulp %st, %st(1) fstpl -8(%ebp) leal -12(%ebp), %eax incl (%eax) jmp .L2 .L3: movl $0, %eax leave ret
Posted by: The Tensor at Aug 4, 2006 5:23:53 PM
Ugh, I'm not used to AT&T assembly syntax for x86. I assume the CPU has an actual floating point unit on it? Oh, are you accumulating multiplications by -1.1, so that you're computing -1.1 to the 10,000,000th power? In that case you're probably spending a lot of time on internal floating point exceptions, which are swamping the other costs.
Posted by: Russell Borogove at Aug 4, 2006 5:40:42 PM
...you're probably spending a lot of time on internal floating point exceptions...
Hmm, that could be. I'll poke at it and see...
Doh! You're right. I changed it to multiply by 10.0 and then by 0.1 in each iteration, incrementing the loop counter by two each time, and it runs in only 100ms. And yes, it's definitely doing two fmulps.
So I guess the original results were closer to the truth. I think I'm going to take this post down later tonight and rewrite it. (I'll leave the comments up as a monument to my shame.)
Posted by: The Tensor at Aug 4, 2006 5:51:57 PM
(I'll leave the comments up as a monument to my shame.)
Not at all. Math is hard.
Posted by: Russell Borogove at Aug 4, 2006 6:13:14 PM
A related site: Language Shootout.
You might consider donating some code to them or at least suggest a new benchmark, if you think it appropriate.
Posted by: E at Aug 5, 2006 11:39:06 AM
I used to be a staunch c++ zealot who despised anything interpreted by fear that exactly the kind of performance drop you described above would happen to me. I thought that it was not that much harder to do c++ when you're used to it and why not do things right to beging with. Then I started grad school in CL and everyone was saying that perl was _the_ language for it. (Heresy!) So eventually they kinda converted me with their LIES. I used perl for a few assignments but ended up doing my thesis in java (a compromise, I guess).
In light of this new evidence I shall return to my proselytizing of the old ways of the c++.
I do wonder what the results would be for java though.
Posted by: BenE at Aug 7, 2006 12:53:02 AM
Use psyco if you want to be fair to python
Posted by: at Aug 7, 2006 9:47:05 PM
The comparison shows up the fact that C++ code is compiled to native data types and uses native machine ops. There is much more indirection going on in the interpreters. If nothing else, perl (and probably python) are providing bignum support on the integer ops.
This sort of thing isn't either languages strong suit. You'll also find these data types take up much more memory than a 32-bit int (they also 'do more'). What these languages *do* do well is to provide richer data types which allow you to perform higher level operations. These higher levels ops (e.g. complex string manipulations) are implemented by nicely tuned C and where you can get good performance.
There are some options for dynamic languages which might handle arithmetic well. I understand that some common lisps (the commercial lisps and probably others e.g. sbcl) both compile to assembler and allow you to add (optional) type decorations so that you can inform the system that you don't care about integer overflow etc for these particular values. Some of the schemes (e.g. stalin) are also very optimisation-focussed.
Also, some of the newer dynamic language VMs will JIT code to assembler and then perhaps get closer to this kind of performance. I know that the parrot engine JITs this sort of thing and you could ask on the perl6 lists if you can do the type decoration thing (I think you can), in that case I'd expect you'd get within-a-small-integer-factor of native performance.
JVMs do a lot of JITting, as does (I think) the MS .net system.
So...if you want native-like performance in a dynamic language, choose one with a modern, JITting VM (not traditional python or perl) and try to find a language which allows optional type decorations (or just has a mad-scary optimiser which doesn't need them).
Posted by: jbert at Aug 8, 2006 1:16:53 AM
Another issue to consider in the Python version is the loop structure. The for and while loop constructs that C programmers know and love incur a significant overhead in Python. The conditions and iterator are evaluated by the interpreter every time around, and the data has to bubble up through the abstaction layers of the interpreted type system.
Many problems can be recast in a functional programming style using "map", where a function is applied to each element in a list. This allows the interpreter to generate machine code for the loop with next to no interpreted overhead. You might consider posting the source to the benchmarks and letting the folks who are interested take a shot at reformulating them into something more amenable to the scripting languages.
The Python wiki has a nice quick overview of tactics to speed things up:
I must admit my frustration that optimization tactics seem to be subtly different in every version of every higher-level language.
Posted by: chrisd at Aug 8, 2006 5:20:28 AM
Earlier someone said:
Perl's scalar datatype is, most fundamentally, a string, and it has to convert to and from numeric types every time it does a math operation. I'm guessing that's the real killer for you.
That's just not true. In Perl, a scalar can be a string or a number (or other things). A scalar can start life as a number ($foo = 1), and it will not be converted to a string until Perl needs its string representation ($foo .= " bar").
Posted by: Dave Rolsky at Aug 8, 2006 6:13:06 AM
I'm a big fan of Python, but since Python doesn't ship with Psyco, I think it's perfectly fair to compare the typical tasks you perform using straight Python vs. whatever. Moreover, while it's good to have a handle on what's a fast way to write code if you need to optimize hot-spots, if you have to write non-Pythonic code all the time to get acceptable performance then you're losing the big advantage Python has in having simple readable code (or maybe I just don't like reading programs where all the loops have been replaced by map or generators....)
Posted by: Joshua Macy at Aug 8, 2006 6:27:32 AM
You might also like to investigate LuaJIT, which can be significantly faster than Perl/Python.
Posted by: Greg Buchholz at Aug 8, 2006 7:07:55 AM
I second the call for posting the benchmarks. :)
As a first time python programmer (like Tensor said he was) there are some nice ways to shoot yourself in the foot performance-wise.
For example:
while i < 1000000:
i += 1
is about 50% slower than:
for i in xrange(1000000):
Posted by: Bob Fleck at Aug 8, 2006 9:17:34 PM
Bob Fleck is right: in an attempt at cross-language consistency, I did use "while i < count" rather than "for i in xrange(count)" in the Python programs. However, when I replace that line in mult.py, the resulting program is slower by almost a factor of four:
time mult.py 10000000
real 0m5.297s
user 0m5.290s
sys 0m0.000s
time newmult.py 10000000
real 0m19.839s
user 0m19.840s
sys 0m0.000s
Posted by: The Tensor at Aug 15, 2006 5:03:09 PM
Below are the Lua versions. These run around 6x/10x/4x faster than Python on my machine with plain Lua. With luajit -O you get another 10x speedup for all of them.
But I agree, the shootout features more applicable benchmarks.
local count = 2*tonumber(arg[1])
local i = 0
while i < count do
i = i + 2
local count = 2*tonumber(arg[1])
local val = 1.0
local i = 0
while i < count do
val = val * 10.0
i = i + 2
val = val * 0.1
i = i + 2
local function func()
local count = 2*tonumber(arg[1])
local i = 0
while i < count do
i = i + 2
Posted by: Mike Pall at Aug 16, 2006 4:09:12 PM
to speed up the python program with a factor of 2 (at least on my PC)
rewrite the python programs so the the variables aren't global anymore
so adder.py becomes
#!/usr/bin/python -u
import sys
def doit(count):
while i < count:
btw : compilation to .pyc only happens for imported modules not for the actual script you run
Posted by: Peter at Sep 8, 2006 3:39:31 AM
Mea culpa on my misstatements about Perl datatypes above -- don't ask what was in my head.
Anyway, I found this lovely site full of cross-language benchmarks today:
Posted by: Russell Borogove at Sep 13, 2006 12:17:59 PM
First, people have been benchmarking C, Perl, and Python like this, there are plenty of other comparisions out there.
Second, please retitle your article to Python vs. Perl vs. C. All of your "C++" programs are able to be compiled w/ a C compiler. If you want to call it C++, declare a class, and call that in the loop, but the simple examples you gave are about as far from C++ code as you can get.
Posted by: John-Mark Gurney at Jul 7, 2007 9:46:44 AM
Python may have native floats, but it's also dynamically typed, so each step through your 'for' loop involves type checking. For fast numerical operations in Python, use NumPy, which doesn't use dynamically-typed elements:
Posted by: Andrew at Jan 26, 2009 11:55:27 AM
I realized that this is an ancient thread; however, I have noticed that perl is about 30-45% faster comparing scalars when you cast them as int(). I am not sure why it is faster, but it makes a big difference.
Posted by: Doug at May 28, 2012 10:29:11 AM


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