Dyalog ’18 Videos, Week 3

The four presentations from Dyalog’18 that we are releasing this week address both the visible (user interface) and invisible (performance) parts of application design. Starting with performance:

“You don’t have to be an engineer to be a racing driver, but you do have to have Mechanical Sympathy.” – former Formula One racing driver Sir John Young “Jackie” Stewart, OBE


This quote was at the heart of the talk by our invited keynote speaker Martin Thompson. In order to write software which performs well, you need to have a basic understanding of how the underlying machinery works. Understanding basic mathematical models for the theoretical throughput of software and hardware helps us take the step from being alchemists to scientists, as we endeavour to write high-performance systems.

Martin takes us for an entertaining stroll through the evolution of modern processors, and some of the maths behind high performance systems. The good news is that systems which make sequential and predictable memory accesses are likely to find sympathy with modern hardware…

Marshall Lochbaum, the most recent addition to the core interpreter team at Dyalog, followed up with a talk on a number of his ideas for increasing the mechanical sympathy of Dyalog APL, to take maximum advantage of branch prediction and other features of modern processors. Some strategies take advantage of runtime inspection of the arguments, something that is more natural in an interpreter with the ability to dynamically select data types, as opposed to strongly typed strategies typically employed by compilers.


TamStat is an application which helps students Tame Statistics. In two talks at Dyalog’18, Stephen Mansour and Michael Baas focus on two different aspects of the user experience. In the first talk, Stephen focuses on the notation available to users of TamStat. Where many statistical libraries contain dozens of strangely named functions with a variety of switches and parameters, TamStat uses a small set of functions, combined with another small set of operators, to provide a very simple but extremely elegant notation for computing probabilities based on a wide variety of distributions. For example:

⍝ Probability that 7 coin flips (0.5 specifying a "fair" coin) will result 
⍝ in at least 3 heads:
7 0.5 binomial probability ≥ 3
⍝ Probability that a number from a normal distribution with a mean of 0 and 
⍝ standard deviation of 1 will be ≤ 3:
0 1   normal   probability ≤ 3

I almost wish I could go back to University and start Statistics 101 again 😊.


Notation is a powerful tool of thought, but graphs make it easier to visualise the results. Following Stephen’s talk, Michael Baas describes work that Dyalog is doing in collaboration with Stephen, with the goal of wrapping TamStat in a modern, HTML/JavaScript based frontend. Current TamStat is based on the ⎕WC (Window Create) library function and is therefore restricted to running on Microsoft Windows. However, many of Stephen’s students use Mac or Linux laptops. The new interface also makes it possible to run TamStat as a web-based service with a web site. We expect that this work will make TamStat accessible to a much wider audience.

Summary of this week’s videos:

Dyalog ’18 Videos, Week 2

Each week until early January, we will be releasing a selection of recordings of presentations from Dyalog’18, which was held in Belfast at the end of October 2018. Last week we kicked off with the opening keynote talks and the prize ceremony and acceptance speech by the winner of our annual problem-solving competition.

Just under half of the presentations at Dyalog User Meetings are by users who have volunteered – or sometimes been commandeered – to share stories about how they have used APL for fun or profit. These user stories provide significant motivation to the Dyalog team for future direction.

Aaron Hsu’s talk on “High Performance Tree Wrangling, the APL Way” is a pearl. Back in 2015 I gave a talk at Google on APL. One of the Google engineers asked about working with trees in APL and I was unable to give him a useful answer. Aaron is working on a compiler for APL, and trees that represent the code that is being compiled are his most important type of data structure.

In this talk Aaron demonstrates that APL is an elegant – and highly efficient – notation for working with trees, if you just pick the right representation!


Most of the talks at Dyalog User Meetings are fairly technical. The subject at the core of Ilaria Piccirilli’s talk – the fair pricing of financial instruments and subsequent evaluation of portfolios – is no exception. Mercifully, Ilaria spares us the details of the calculations – as she dryly notes, there is no “Fair Pricing for Dummies”. Instead, she offers humorous insights into the way her team used APL to deal with the explosion of computations required by regular additions to legislation requiring health checks – and the day that negative interest pulled the rug out from under most standard pricing calculations.

The other, slightly larger half of the talks at Dyalog Users meetings are by members of the Dyalog Team, talking about work that has recently been done on our products or presenting designs for future enhancements.


Adám Brudzewsky’s talk, titled Array Notation Mk III, is about a potential future extension to the APL language, which will make it possible to easily and clearly describe arrays of high rank, or with deeply nested structure, without using APL primitives to “construct” them, as is common practice today. In addition to making application code easier to read and write, a literal notation for data structures will make it easy to use text files to describe data structures which are essentially part of the source code of an application, and should be managed by a source code management system. As the name suggests, this work has been ongoing for some time, with the initial inspiration coming from a user presentation by Phil Last, back at Dyalog ’15 in Sicily. Watch the presentation and give us feedback on whether you think this idea is now sufficiently baked to become part of Dyalog APL, or we’ll need a “Mk IV” talk next year!


With the growth in usage of Dyalog APL under macOS and Linux – especially in server or cloud environments – the Dyalog Remote Integrated Development Environment is becoming a “mainstream” tool, rather than the curiosity that it was during the first few years of development. Our partners at Optima Systems are developing RIDE on Dyalog’s behalf, and Gilgamesh Athoraya is now the lead developer. In his talk on “RIDE 4.1 and Next Generation Integrations”, Gil talks first about significant new features and performance improvements to RIDE in 4.1 – and then continues to talk about how components of the RIDE technology may be re-purposed to provide APL add-ins for popular development frameworks like the new Microsoft VS Code.

Summary of this week’s videos:

Diane’s Lasagne Problem

Making Lasagne

Participants in the SA2 Performance Tuning workshop at the Dyalog ’18 User Meeting were encouraged to bring their own problems for the group to work on. Diane Hymas of ExxonMobil brought a good one. The one-liner computation is as follows:

lasagne0 ← {groups {+⌿⍵}⌸ amts ×[⎕io] spices[inds;]}

where

   n ← 8e5
   spices ← ?6000 44⍴0
   groups ← +\(16↑1 2)[?n⍴16]
   inds   ← ?n⍴≢spices
   amts   ← ?n⍴0

Applying lasagne0 to this dataset:

   ⍴ lasagne0 ⍬
100015 44
   ≢ ∪ groups
100015

   )copy dfns wsreq cmpx

   wsreq 'lasagne0 ⍬'
844799820
   cmpx  'lasagne0 ⍬'
2.12E¯1

The problem with lasagne0 is space rather than time. The 845 MB required for this dataset may be acceptable, but we can be called upon to cook up large batches of lasagne in a smallish workspace, on a machine with limited RAM. (Large n and large ≢∪groups.)

All benchmarks in this document were run in Dyalog APL version 17.0, in a 2 GB workspace, on a machine with generous RAM.

Solutions

Marshall Lochbaum solved the problem. The alternative solutions are as follows:

lasagne0 ← {groups {+⌿⍵}⌸ amts ×[⎕io] spices[inds;]}
lasagne1 ← {↑ (groups{⊂⍵}⌸amts) {+⌿⍺×[⎕io]spices[⍵;]}¨ groups{⊂⍵}⌸inds}
lasagne2 ← {↑ (groups{⊂⍵}⌸amts)      {⍺+.×spices[⍵;]}¨ groups{⊂⍵}⌸inds}
lasagne3 ← {↑ {amts[⍵]+.×spices[inds[⍵];]}¨ {⊂⍵}⌸groups}

lasagne0 is the original expression; lasagne1 and lasagne2 were derived by Marshall during the workshop; lasagne3 was suggested by a participant in the workshop. The four functions produce matching results. Comparing the space and time:

space (MB)           time
lasagne0 845 2.29e¯1 ⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕
lasagne1 74 3.60e¯1 ⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕
lasagne2 74 2.39e¯1 ⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕
lasagne3 74 2.93e¯1 ⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕

lasagne0 v  lasagne1

Nearly all of the space required to evaluate lasagne0 is accounted for by the space for computing the right argument to key:

   wsreq 'lasagne0 ⍬'
844799820

   wsreq 'amts ×[⎕io] spices[inds;]'
844799548

In fact, the array spices[inds;], all by itself, is already very large. It has shape (⍴inds),1↓⍴spices (≡ 8e5 44), each item requiring 8 bytes.

   wsreq 'spices[inds;]'
281599556

   ⍴ spices[inds;]
800000 44

   8 × ×/ ⍴ spices[inds;]
281600000

   qsize←{⎕size '⍵'}    ⍝ # bytes for array ⍵
   qsize spices[inds;]
281600040

lasagne1 avoids creating these large intermediate results, by first partitioning the arguments (groups{⊂⍵}⌸amts and groups{⊂⍵}⌸inds) and then applying a computation to each partition. In that computation, the operand function {+⌿⍺×[⎕io]spices[⍵;]}, is a partition of amts and is the corresponding partition of inds.

lasagne1, lasagne2 and lasagne3 require the same amount of space to run, so the comparison among them is on time.

lasagne1 v  lasagne2

The only change is from +⌿⍺×[⎕io]spices[⍵;] to ⍺+.×spices[⍵;], which are equivalent when is a vector. The interpreter can compute +.× in one go rather than doing +⌿ separately after doing ×[⎕io]; in such computation the interpreter can and does exploit the additional information afforded by +.× and is faster by a factor of 1.5 (= 2.39 ÷⍨ 3.60).

lasagne2 v  lasagne3

The idea in lasagne3 is doing one key operation rather than the two in lasagne2. Therefore, the changes between lasagne2 v lasagne3 are:

lasagne2 groups{⊂⍵}⌸amts
groups{⊂⍵}⌸inds
spices[⍵;]
lasagne3 {⊂⍵}⌸groups amts[⍵] spices[inds[⍵];]

All three key operations involve {⊂⍵}⌸ with groups as the key, and are roughly equally fast, each taking up no more than 7% of the total time.

   cmpx 'groups{⊂⍵}⌸amts' 'groups{⊂⍵}⌸inds' '{⊂⍵}⌸groups'
  groups{⊂⍵}⌸amts → 1.69E¯2 |   0% ⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕
* groups{⊂⍵}⌸inds → 1.39E¯2 | -18% ⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕
* {⊂⍵}⌸groups     → 1.36E¯2 | -20% ⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕⎕

lasagne3 is doing one less key operation than lasagne2 in exchange for doing, for each of the ≢∪groups (= 100015) executions of the operand function, amt[⍵] v and spices[ind[⍵];] v spices[⍵;]. Indexing is by no means slow, but it’s not as fast as references to and . Therefore, lasagne2 is faster.

The trade-off may differ for different values of groups. In this case groups are small-range integers so operations using it as the key value are fast.

Welcome to the Dyalog ’18 Videos!

Three weeks have gone by since we waved goodbye to the last Dyalog ’18 delegates in Belfast. We’ve had time to catch up on sleep, half of us have had colds and recovered from them. Jason Rivers and Richard Park have started mixing and improving the audio and video recordings, and we are ready to release the first group of processed videos.


Our plan is to release batches of 3-5 videos, with enough variety for everyone to find at least one topic of interest each week. We have not reviewed all of the material yet; there are always one or two where something went wrong and we are unable to publish the recordings (or the presenter asks that we refrain from making the talk public), but we do expect to be able to make the vast majority of the talks available over the next couple of months.

Each week, I’ll be doing my best to introduce each set with a blog entry: The first batch contains cleaned-up versions of the presentations that were streamed live from Belfast. The audio and video quality is significantly enhanced compared to the live stream, and the most confusing gaffes in my own live demo have been removed 😊.


As usual, the user meeting opened with the traditional trio of keynotes by Dyalog’s CEO Gitte Christensen, the CXO Morten Kromberg (that’s me) and CTO Jay Foad. Gitte introduces a couple of new faces at Dyalog, and the contest winners, so everyone can plan to buy the winners drinks during the week. Gitte then discusses high level direction – announcing our intention to make the Linux version available to download, and included in public Docker containers and Cloud VM images, with no questions asked.


My own session mostly consists of a live demo of the potential consequences of making Linux licences really easy to get hold of. In an imaginary conversation with a data scientist, I demonstrate the use of Dyalog APL to implement an (admittedly silly) analytical function, and subsequently make it available as a web service and via a web site, finally deplying it to the cloud using a set of Public Docker containers, without once installing Dyalog APL itself.


Jay Foad rounded Monday’s live stream off with a review of the features of the recently released version 17.0, before moving on to talk about the work that the development team is planning for versions 17.1 and 18.0, scheduled for the spring of 2019 and 2020, respectively.


In accordance with tradition, we also streamed the Prize Ceremony for the International Problem-Solving Competition and – often the most interesting talk of the year – the acceptance speech where this year’s winner talked about his code, and the experience of learning APL. This year’s winner did not let us down; it is amazing how quickly you can learn to write really, really good APL code!

Summary of this week’s videos:

Rencontres Dyalog APL 2016 – Paris, France

It is really good to see APL events come back to life! In April of 2014, we witnessed the re-birth of SWEDAPL, which had been dormant for some time – but now meets twice a year and is perhaps the most vibrant APL meeting on our circuit, with many young developers developing new products and features in APL. The last SWEDAPL meeting drew a substantial international crowd, including a number of Danes – and the next one, scheduled for April 1st, is making a guest appearance in Copenhagen, hosted by Simcorp A/S – a bit like the Tour de France 🙂

paris16This year we are really happy to be back in France, which has also had a relatively dormant APL community for the last decade or so – at least in terms of holding meetings. In this case we decided to arrange a meeting with the help of our French distributor – Quantys. Although the invitation was to a “Dyalog User Meeting“, about half of the attendees were users of other APL systems than Dyalog APL – with a little luck this meeting will turn out to contain the seeds for a rebirth of an independent French APL group. Fingers crossed!

Everyone please note: If you want to organise a local APL event, and you invite a speaker from Dyalog, we will do everything we can to send one or two delegates to your meeting. The current “circuit” includes Finland, Germany and Sweden twice a year, France and the East Coast USA. We have been known to show up at the Bay Area Users’ Group from time to time, in Toronto, at J and kx meetings – and recently also at FunctionalConf in Bangalore.

After welcoming remarks from Marc Righetti of Quantys, Gitte talked about Dyalog’s commitment to ensure that APL is well-integrated with modern computing platforms and infrastructure, which is always in the throes of another revolution. The current movement towards cloud computing and the need for platform independence is no exception. The good news is that Dyalog is growing to meet the challenge; we expect to add another couple of heads this year and grow the company by another ten percent.

Dan Baronet is a native of Montreal, Canada. As one of our French-speaking team members, he ended up doing most of the heavy lifting, with presentations on the upcoming v15.0 release, and a recap of the recent language enhancements in version 14.0 – in particular, the rank and key operators and function trains. Nicolas Delcros also spoke in French on the subject of his most recent work on integrating the publishing capabilities of Adrian Smith’s NewLeaf tool to SharpPlot, under the name SharpLeaf. I was only allowed to interrupt the flow of French twice, first with a road map presentation and, in the afternoon, a brief introduction to Futures and Isolates.

At the end of an action-packed day, Quantys treated us all to Champagne and snacks – many thanks to Marc for running the show and taking good care of us. A single day was much too short a time to do justice to the last decade of Dyalog achievements – so we will have to be back more regularly!

FinnAPL Forest Seminar 2016

The view from the Sauna. Some people actually went in!

The view from the Sauna. Some people actually went in!

Finns probably have better reasons to look forward to spring more than most of us: not only does it get much easier to keep that hole in the ice open, it is time for the annual FinnAPL Forest Seminar!

This year, just under 20 of us gathered for two days (Thursday March 10th and Friday March 11th) at Hirvihaara Manor, about an hour north of Helsinki, to update each other on what we have been getting up to recently.

Thursday

After a warm welcome from Jouko Kangasniemi, Chairman of FinnAPL, Veli-Matti Jantunen from Statistics Finland kicked the proceedings off with a talk titled “The long way of an APL2 bigot to Dyalog world”, where he discussed features of recent versions of Dyalog APL, awarding some of them them varying numbers of thumbs up, declaring some to be irrelevant. A few were found to be flawed… We are hoping to talk him into a repeat at Dyalog’16 as this was a valuable and thought-provoking review!

I was on next – with the Spring 2016 version of the Dyalog Road Map. As should be confirmed by the slides, there is not a big change in direction. We are planning to increase headcount by another 10% this year and continue investing in the core interpreter technology, APL compilers, and tools to help you build applications on a growing number of platforms.

Ants on the left. Ray Cannon on the right

Ants on the left. Ray Cannon on the right

After lunch, Ray Cannon showed us how to “Build a better ant brain”, producing wonderful, coloured, animations with ants crawling all over the big screen, using MiServer 3.0 and a bit of JavaScript – running under Dyalog APL on a Raspberry Pi!

My technical keynote in the morning had included a demo of a very early prototype of a Python interface, which will allow APL users to tap in to Python libraries. I was, therefore, very interested in the next presentation by Esa Pursiheimo from the VTT Technical Research Centre of Finland – which gave us all an introduction to the Python language. There is no question that the Python community has built libraries that could be very useful to APLers (although I cannot say the language itself impressed me much 🙂 ).

The last presentation of the day, titled “Data Driven Documents” (aka “D3”), was also about using libraries written in other programming language to extend APL applications. In this case the language was JavaScript. Jouko Kangasniemi from the Confederation of Finnish Industries (EK) showed how he is generating JavaScript to call the popular D3 Graphics Library and publish charts that are relevant to Economic planners in Finland. A collection of animated charts created using this technology can be found at http://ek.fi/materiaalipankki/tietografiikka/talous/viikon-graafit/.

Since we were in Finland, the afternoon ended with a visit to a traditional “smoke sauna”, before we all scrubbed up for the banquet.

Cheers! From left to right (more or less): Antero Ranne, Gitte Christensen, Esa Lippu, Miika Rämä, Simo Kilponen, Jouko Kangasniemi, Heikki Viitamäki, Esa Pursiheimo, Olli Paavola, Kaarlo Reipas, Göran Koreneff, Morten Kromberg, Kimmo Kekäläinen, Veli-Matti Jantunen, Timo Korpela, Ray Cannon (Missing: Anssi Seppälä)

Cheers! From left to right (more or less): Antero Ranne, Gitte Christensen, Esa Lippu, Miika Rämä, Simo Kilponen, Jouko Kangasniemi, Heikki Viitamäki, Esa Pursiheimo, Olli Paavola, Kaarlo Reipas, Göran Koreneff, Morten Kromberg, Kimmo Kekäläinen, Veli-Matti Jantunen, Timo Korpela, Ray Cannon (Missing: Anssi Seppälä)

Friday

The first talk on Friday morning was perhaps the most interesting from my point of view: Antero Ranne of the Ilmarinen Mutual Pension Insurance Company: Parallel showed how he was able to speed up financial simulations by a factor of approximately 3 on his Intel i7-based laptop, using Futures and Isolates in Dyalog version 14.0. It is really good to see that domain experts wield this tool!

After coffee, Gitte presented the work that she had done to put APL on the map as an invited speaker at a recent conference on the history of information technology in the Nordic region. She also reminded us all that we will be celebrating the 50th anniversary of the first running APL system on November 27 (http://silvermapleweb.com/first-cleanspace/). At Dyalog ’16 on October 9th-13th in Glasgow, Scotland, Dyalog will set time aside to celebrate this anniversary in collaboration with the British APL Association. If you have a good story about ground-breaking work done in APL in the early days, please get in touch and discuss how you might contribute to the celebrations!

Once again, I found myself standing between the audience and lunch – fortunately there are enough juicy language features and interfaces coming in versions 15.0 and 16.0 and I did not have anyone walk out before I was done. I even had time to talk about a workspace that we added several years ago, after discovering that several members of the audience were unaware of it: The “loaddata” workspace, which contains functions to read and write Excel Spreadsheets, CSV files, XML and ODBC data sources. If you have not seen it yet, try loading it and take a look.

After another excellent lunch, Anssi Seppälä of Enease Oy wrapped up the formal part of the programme with a talk on an inverted vectorial database implemented in the J programing language, named JD. JD makes it straightforward to manage large timeseries containing records of power usage and the quality of electricity delivered to consumers, perform analyses and generate visualisations of the data.

Several of us continued discussing programming challenges, while drinking (STRONG!!!) Finnish coffee and eating the wonderful cakes that were provided all day by Hirvihaara Manor, before heading back home after another successful FinnAPL Forest Seminar – we look forward to the 2017 edition!

Gitte and I managed to get about 40 hours at home before boarding the next plane, heading for Paris for the first French Dyalog User Meeting in recent history. More about that coming soon!