Freely available online at http://developer.nvidia.com/object/gp.... Going through this since I've been doing so much GPU-offloading of multibody simuFreely available online at http://developer.nvidia.com/object/gp.... Going through this since I've been doing so much GPU-offloading of multibody simulation code recently, and the project I'm starting regarding red blood cell flow will make extensive use of Tesla supercomputers....more
solid, but there's plenty better. excellent coverage of the solaris-specific tools.solid, but there's plenty better. excellent coverage of the solaris-specific tools....more
An instant classic, and a logical follow-up to P&H's Computer Architecture A Quantitative Approach. A necessary read for all modern computer architectAn instant classic, and a logical follow-up to P&H's Computer Architecture A Quantitative Approach. A necessary read for all modern computer architects. --- Bah, got shafted on that first purchase. Let's try this again, players. Amazon third party, 2010-04-18. --- Amazon third party, 2009-11-13....more
Wish I had this to prepare for the CS GRE come saturday, but even Amazon hasn't the power to get it to me by then. Oh well! I really doubt it (the tesWish I had this to prepare for the CS GRE come saturday, but even Amazon hasn't the power to get it to me by then. Oh well! I really doubt it (the test)'s going to get down and dirty into foundations of computation, but I've never even read Rogers's Theory of Recursive Functions and Effective Computability, and found Sorbi too difficult to bother with at the time...:/ ugh!...more
Hahha, I was telling someone the other day, "the thing about Chaitin is that every book I've read by him points out, not once but several times, that Hahha, I was telling someone the other day, "the thing about Chaitin is that every book I've read by him points out, not once but several times, that he thinks himself the third in a line going back through Turing to Gödel. This makes him not only the greatest living computer scientist, but the greatest computer scientist of all time, Turing being a mathematician and Gödel a logician. They (his books) can get very messianic at times, but without the humility we've associated since Golgotha with a Deliverer -- think of a very unhappy universe where Michio Kaku had written more than autohagiographic pop science balderdash and a forgettable quantum chromodynamics textbook. He'd want fucking statues set up, and seven comely maidens of virtue true each nine years." And what would be the one-line Amazon intro:
More than half a century has passed since the famous papers GÖDEL (1931) and TURING (1937) that shed so much light on the foundations of
I'd put a dollar on a self-mention within forty words from there....more
Amazon 2009-06-17. Wow, this is *REALLY GOOD* so far, definitely the best of several computational complexity books I've ever read (as the first majorAmazon 2009-06-17. Wow, this is *REALLY GOOD* so far, definitely the best of several computational complexity books I've ever read (as the first major publishing event in complexity theory since Aaronson's development of the Complexity Zoo, perhaps there was a higher bar to leap). Seventeen thirty-two, personal note: my signature lifts a quote from the Complexity Zoo:
Nondeterministic Polynomial-Time: The class of dashed hopes and idle dreams...
The book was clearly designed with the assumption that Sipser's modern classic Introduction to the Theory of Computation would be used as an undergraduate precursor; besides referencing Sipser several times early on (and his role heading up MIT's Math department, a group the authors are -- from the Foreward -- definitely good pals with (the authors themselves hail from Princeton, where I had no idea but Brian Kernighan and Robert Sedgewick are still faculty (of course I knew Andrew Appel, Edward Felten, and Robert Tarjan were still there, and Andrew Yao/Richard Lipton's emeritus status (but we've got Lipton now, motherfuckers!)))). The book takes off almost directly from where Sipser's study of complexity ends, with a deep study of p≤ polynomial-time Karp reducibility (well, actually it starts with deterministic TM's, but as I've studied the 7-parameter TM formalism since I was thirteen or so, I didn't look at Chapter 1 too closely (I *do* applaud their Claim 1.6: single-tape simulation of k-tape TM's in time 5kT(n)^2 -- this kind of rigorous, strong presentation is welcomed -- and ESPECIALLY the early presentation of oblivious Turing Machines (those which care only about the input length, not the input content), as this simplifies many a proof later on (most authors, if they introduce OTM's at all, do so only as a curiousity and not as a fundamental proof mechanism))). The heavy emphasis throughout on the dual miracles of randomization and modern crypto (including more advanced topics like derandomization, the probabilistic complexity classes, pseudorandomization and hardness amplification) will hopefully result in these topics being more deeply embedded within classical theory classes, as they should be. Furthermore, being placed (for the first time?) on the same footing as automata and the Hierarchy means that relevant issues are addressed throughout -- the implication that P == NP, for instance, would mean that nothing is to be gained from randomized algorithms, was entirely new to me *despite* having taken Lipton's Randomized Algorithms class and having read both of the two major books on the subject (Motwani + Raghavan and Mitzenmacher + Upfal). I can fairly say that realizing this obvious truth blew my mind.
The book has wonderful quotes heading each chapter, which I just can't say enough about. Computer scientists don't know nearly enough of the rich history of their study (I'm regularly scandalized when I run into graduate students -- not the ladies and man-ladies in things like Human-Computer Interaction, but real apprentice computer scientists -- who don't know the names of Church, Rabin, Aho, Hamming and Hoare. I want to punch these ingrates in the face), and things like this can only help. The bibliography and citations are kind of sparse, but the important ones are there, and the authors are as current with the literature as one would hope (I was pleased to see the newly-seminal AKS2004 referenced early on).
Be sure to check out section 2.7.3, "The P == NP Utopia", for a special treat -- coverage of the implications of that most foul heresy, the majority of which I'd heard elsewhere, but only as single, whispered perversions -- with a look forward to chapter 5, its coverage of the polynomial hierarchy, and a surprise or two regarding MIN-EQ-DNF (btw, if you've never read it, Aaronson's tongue-in-cheek "Polynomial Hierarchy Collapses" is one of the funniest things ever written).
One comment -- the exercises, so far, are both really fucking weird and really fucking difficult. I am not sure I'd want to use this book's problem sets as self-study; classics like Papadimitriou are still the best in this arena, IMHO.
I'm not yet done, and this might yet get its fifth star -- we'll see. What is certain, however, is that there is a new standard reference for undergraduate and graduate students, researchers and professionals interested in the majestic sweep of complexity theory, and its authors are Sanjeev Arora and Boaz Barak....more
Totally seminal. An excellent textbook (probably the only acceptable one) for a graduate class in the theory of parallel computation (though Arora+BarTotally seminal. An excellent textbook (probably the only acceptable one) for a graduate class in the theory of parallel computation (though Arora+Barak's 2009 opus Computational Complexity A Modern Approach has equally rich coverage of Nick's Class), especially as it applies to the PRAM model. Greenlaw et al provide a fine survey of computing theory as adjusted for the parallel model, including approximation algorithms (see Vazirani's Approximation Algorithms for more detail), a proof of the circuit value problem as P-complete, evidence that NC != P, NCk Turing reducibility, etc. Part II is formed of an excellent compendium of P-complete and open problems, including some from formal languages, real analysis, CC (stable marriage CCVP, LFMM, etc) and RNC (blocking flow in a 3-layered network, 0-1 maxflow, subtree isomorphism, etc), making this an invaluable companion to Garey+Johnson's classic Computers and Intractability A Guide to the Theory of NP-Completeness. References to the literature are broad and deep.
My only complaint relates to the publication date of November 1994; this preceded the circa-2004 Pentium 4 "Tejas" and "Jayhawk" frequency-chasing madness (see Sprangle and Cormean's paper, "Increasing Processor Performance by Implementing Deeper Pipelines", and my presentation looking back upon it). The authors make reference to Amdahl's and Gustafson's Laws, but not to the dynamic power equation (P = αCV2F), the effects of branch mispredictions, nor the memory wall, though it is these which have motivated a general move to multi- and manycore architectures.
Of course, this book was written shortly after the Pentium's original release. Sun's SPARC architecture had not yet moved to the 64-bit V9. P5 frequencies were just beginning their race to 1GHz (and a 20+ stage pipeline; recall that the 486 had a classic 5-stager). I was 14 -- if I recall correctly, I was still fighting with DOS 6.22's HIGHMEM.SYS HMA driver and trying to tell the difference between EMS and XMS. Hell, the RISC-vs-CISC debate had yet to be settled (that would wait for the Pentium II's "CRISC" ISA + P6 µarch), and even second-level caches seemed luxuries outside of the NSA, LLNL/LANL and NOAA (and would remain so for those unfortunate purchasers of Intel's Celeron P6, sheesh). For Chrissakes, MMX had yet to even add (poor) SIMD capability to x86 (nevermind that x86 SIMD was utter shit until SSE2). Patterson and Hennessy's seminal Computer Architecture A Quantitative Approach was in its first edition. It was a completely different world of computer architecture. For that matter, this is not (and never pretends to be) an Architecture book; this reviewer simply suffers from being a much more competent architect than theorist :D.
Well worth reading. I know nothing similar (though I have not yet read Quinn's Parallel Computing Theory and Practice, which I only heard about while writing this review). Unceasing thanks to Professor Rich Vuduc for getting me into this field! --- updated Tue Mar 2 04:40:40 EST 2010 finally went on sale, snagged for $9.62 woo-hah despite $275 list --- assembling necessary prerequisites for the Good Work aka thesis...it's gonna be a monster muh wa hahahha I'm the HNIC...more
I'm more excited about this than any textbook I've read all year. It's absolutely awesome thus far. Kolmogorov complexity is so deep in computer scienI'm more excited about this than any textbook I've read all year. It's absolutely awesome thus far. Kolmogorov complexity is so deep in computer science -- in a way, I feel that it *is* computer science, i.e. "necessary and sufficient" as we dorks like to say -- yet understood or even known by so few. I'm hoping that when done with this, my understanding of my discipline will be as broadened and freshened as it was upon reading classics like Hennessy and Patterson's Computer Architecture A Quantitative Approach, Van Roy and Haridi's Concepts Models and Techniques of Computer Programming, Pierce's Types and Progamming Languages, or indeed even Dijkstra's A Discipline of Programming.
Nothing will ever compare to first looking into SICP, though :D.
I'm expecting some hard slogging, but it's wonderfully written thus far. A real treasure....more
Free PDF (Thanks, Dr. Chaitin!), 2009-05-01. What better way to celebrate May Day than with this classic ball-buster? My Livejournal's long closed, buFree PDF (Thanks, Dr. Chaitin!), 2009-05-01. What better way to celebrate May Day than with this classic ball-buster? My Livejournal's long closed, but I've been thinking of starting a purely technical blog; this book shows up in tonight's inaugural post....more
This is the new best book on string algorithms, replacing Navarro's Flexible Pattern Matching in Strings at the top. Actually, picking Navarro up, spiThis is the new best book on string algorithms, replacing Navarro's Flexible Pattern Matching in Strings at the top. Actually, picking Navarro up, spinning him around a few times, and hurling him into a pit through which he falls for five-thousand years (and I *really* liked Navarro's book -- it totally set my efforts at the job (then Reflex Security, where I was building the Reflex Interceptor IPS) in a new direction back in 2003). One of the best computer science textbooks I've ever seen. If you do string algorithms, this ought be the first book on your shelf. ------ Amazon 2008-12-30. I bit the bullet and grabbed a new copy -- I didn't want 2008 to close without securing what promises to be a rare and exquisite treat. Maxime Crochemore (link de-Gaullized for your pleasure) is certifiably: da man, and a delighted stringalg community has been waiting for this with breath bated.
(was: YAY! Crochemore published in 2006 my favorite text on combinatorial matching, Jewels of Stringology (with Wojciech Rytter). Between Crochemore, Rytter and Navarro, Old Europe and South America are pulling ahead in the combinatorial automata racket...I intend to change all that, though =) (malicious grin). Anyway, this is sure to be an epic treatment of my all-time most beloved area of algorithms, with likely applications to my day-to-day work both in the laboratory and at the office.)...more
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