<html><head><meta http-equiv="Content-Type" content="text/html; charset=us-ascii"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;" class="">The list of mentors for this project looks great to me. I am not sure if I can add much other than I think this is a nice project. Perhaps it would be best to get the advice of some of the mentors?<div class=""><br class=""></div><div class="">For some very simple tests with an ODE solver, I concluded that accelerate can perform at least as well as Julia. It would certainly be very helpful to be able to get Jacobians for ODE solving and for other applications.</div><div class=""><br class=""><div class="">
<div style="color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px; font-style: normal; font-variant-caps: normal; font-weight: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px;">Dominic Steinitz</div><div style="color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px; font-style: normal; font-variant-caps: normal; font-weight: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px;"><a href="mailto:dominic@steinitz.org" class="">dominic@steinitz.org</a></div><div style="color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px; font-style: normal; font-variant-caps: normal; font-weight: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px;"><a href="http://idontgetoutmuch.wordpress.com" class="">http://idontgetoutmuch.wordpress.com</a></div><div style="color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px; font-style: normal; font-variant-caps: normal; font-weight: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px;">Twitter: @idontgetoutmuch</div><div style="color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px; font-style: normal; font-variant-caps: normal; font-weight: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px;" class=""><br class=""></div><br class="Apple-interchange-newline">
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<div><br class=""><blockquote type="cite" class=""><div class="">On 24 Mar 2018, at 17:20, Charles Blake <<a href="mailto:cb307@st-andrews.ac.uk" class="">cb307@st-andrews.ac.uk</a>> wrote:</div><br class="Apple-interchange-newline"><div class=""><div id="divtagdefaultwrapper" dir="ltr" style="font-style: normal; font-variant-caps: normal; font-weight: normal; letter-spacing: normal; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; word-spacing: 0px; -webkit-text-stroke-width: 0px; font-size: 12pt; font-family: Calibri, Helvetica, sans-serif;" class=""><p style="margin-top: 0px; margin-bottom: 0px;" class=""></p><div class="">Thanks for the response Michal,</div><div class=""><br class=""></div><div class="">Yes, this did cross my mind - and I wouldn't be expecting to outperform those frameworks in the timeframe available! I assumed that the reason that this project was suggested was perhaps:</div><div class=""><br class=""></div><div class="">a) there is some intrinsic value in implementing these algorithms natively in haskell (hence why the 'ad' library was developed in the first place), so that those who want to use parallel automatic differentiation / the machine learning algorithms built on top of it can do so without leaving the haskell ecosystem,</div><div class=""><br class=""></div><div class="">and b) because the challenges involved in implementing parallel ad in a purely functional language are a little different to those involved in doing so in OO/imperative languages - so it might be interesting from that angle as well?</div><div class=""><br class=""></div><div class="">So perhaps my aim would no be to do something unique, but rather to do something that has already done well in other languages, but has not yet been provided as a haskell library. Does this sound like a reasonable approach or do I need to find a slightly more unique angle?</div><div class=""><br class=""></div><div class="">Thanks,</div><div class="">Charlie</div><p style="margin-top: 0px; margin-bottom: 0px;" class=""></p></div><hr tabindex="-1" style="font-family: Helvetica; font-size: 12px; font-style: normal; font-variant-caps: normal; font-weight: normal; letter-spacing: normal; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; word-spacing: 0px; -webkit-text-stroke-width: 0px; display: inline-block; width: 617.390625px;" class=""><span style="font-family: Helvetica; font-size: 12px; font-style: normal; font-variant-caps: normal; font-weight: normal; letter-spacing: normal; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; word-spacing: 0px; -webkit-text-stroke-width: 0px; float: none; display: inline !important;" class=""></span><div id="divRplyFwdMsg" dir="ltr" style="font-family: Helvetica; font-size: 12px; font-style: normal; font-variant-caps: normal; font-weight: normal; letter-spacing: normal; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; word-spacing: 0px; -webkit-text-stroke-width: 0px;" class=""><font face="Calibri, sans-serif" style="font-size: 11pt;" class=""><b class="">From:</b><span class="Apple-converted-space"> </span>Michal J Gajda <<a href="mailto:mgajda@mimuw.edu.pl" class="">mgajda@mimuw.edu.pl</a>><br class=""><b class="">Sent:</b><span class="Apple-converted-space"> </span>24 March 2018 16:56:35<br class=""><b class="">To:</b><span class="Apple-converted-space"> </span>Dominic Steinitz; Marco Zocca; <a href="mailto:accelerate-haskell@googlegroups.com" class="">accelerate-haskell@googlegroups.com</a>; Charles Blake; <a href="mailto:haskell-cafe@haskell.org" class="">haskell-cafe@haskell.org</a><br class=""><b class="">Subject:</b><span class="Apple-converted-space"> </span>Re: Accelerating Automatic Differentiation</font><div class=""> </div></div><div style="font-family: Helvetica; font-size: 12px; font-style: normal; font-variant-caps: normal; font-weight: normal; letter-spacing: normal; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; word-spacing: 0px; -webkit-text-stroke-width: 0px;" class=""><div class=""><div dir="auto" class="">Hi Charlie</div><div dir="auto" class=""><br class=""></div><div dir="auto" class="">It certainly looks like exciting project, but the bar is currently placed very high.</div><div dir="auto" class="">TensorFlow package not only provides automatic differentiation for whole programs, but also optimizes data processing both on GPU, and reading to achieve large batches.</div><div dir="auto" class="">This field has a lot of hot developments, so You would either need to propose something unique to Haskell, or You risk being outclassed by PyTorch and TensorFlow bindings</div><div dir="auto" class=""> Maybe Dominic suggests something too.</div><div dir="auto" class=""> Cheers</div></div><div class=""><div dir="auto" class=""> Michal</div></div></div></div></blockquote></div><br class=""></div></body></html>