Computer Architecture, Fifth Edition: A Quantitative Approach (2011)(dl.acm.org)
dl.acm.org
Computer Architecture, Fifth Edition: A Quantitative Approach (2011)
https://dl.acm.org/doi/book/10.5555/1999263
10 comments
I just discovered that this book by John L. Hennessy & David A. Patterson is freely available from ACM, so just wanted to share it. I came across it by reading this thread from three weeks ago: https://news.ycombinator.com/item?id=42157558
The 5th edition is seriously out of date. The last 15 years or so have seen massive changes in computer architecture, in particular the explosion of all manner of hardware accelerators, including modern GPUs.
The 7th edition is supposed to come out on 1 January 2025.
The 7th edition is supposed to come out on 1 January 2025.
> seriously
How seriously though? Also, the priniples behind GPUs and their use - unlike maybe their physical realization - have not changed much since 2011. (See Chapter 4.)
How seriously though? Also, the priniples behind GPUs and their use - unlike maybe their physical realization - have not changed much since 2011. (See Chapter 4.)
It's a gift horse, and you say it needs dental work? ;-)
I think most of the essentials remain true today. As for hardware accelerators, they're all some variation of SIMD or an ASIC built to run a specific algorithm.
Von Neumann stuck us with the program counter, and all the waiting that comes along with it. It's almost impossible to walk away from his legacy.
I think most of the essentials remain true today. As for hardware accelerators, they're all some variation of SIMD or an ASIC built to run a specific algorithm.
Von Neumann stuck us with the program counter, and all the waiting that comes along with it. It's almost impossible to walk away from his legacy.
> Von Neumann stuck us with the program counter
As opposed to what? A stack of program counters? A set of registers containing program counters? Von Neumann seems related to this as much as the fact that you can only beat one person with a single stick.
As opposed to what? A stack of program counters? A set of registers containing program counters? Von Neumann seems related to this as much as the fact that you can only beat one person with a single stick.
Look at tagged token architecture - no program counter required.
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It's actually bad news for students when expensive textbooks get updated who go to classes with assignments based on a specific edition and their indices get reshuffled and the old editions become useless even though the core stuff which are unchanged are really the only relevant subset to the syllabus.
> The last 15 years or so have seen massive changes in computer architecture, in particular the explosion of all manner of hardware accelerators, including modern GPUs.
What mechanics would you like the eighth edition to introduce?
What mechanics would you like the eighth edition to introduce?
This book ( or rather a much older edition ) literally changed my life, by essentially teaching me that the whole of a computer was about measurable tradeoffs, from hardware to software.
The fact that it was true for hardware as well hadn’t been obvious to me till then, coming from a math background and being a self taught coder.
The beauty in this is that you can then build systems that fly if you understand the tradeoffs of all your layers, and make sure you fall on the right side of each of them.
Rather unsurprisingly, I ended up doing HPC, where this is all pretty obvious, but I strongly believe that this is true for all software.
The fact that it was true for hardware as well hadn’t been obvious to me till then, coming from a math background and being a self taught coder.
The beauty in this is that you can then build systems that fly if you understand the tradeoffs of all your layers, and make sure you fall on the right side of each of them.
Rather unsurprisingly, I ended up doing HPC, where this is all pretty obvious, but I strongly believe that this is true for all software.
Personally, I recommend "Computer Organization and Design - The Hardware Software Interface" by Patterson and Hennessy. From it's preface (regarding this book):
Some readers may be familiar with Computer Architecture: A Quantitative Approach, popularly known as Hennessy and Patterson. (This book in turn is often called Patterson and Hennessy.) Our motivation in writing the earlier book was to describe the principles of computer architecture using solid engineering fundamentals and quantitative cost/performance tradeoffs. We used an approach that combined examples and measurements, based on commercial systems, to create realistic design experiences. Our goal was to demonstrate that computer architecture could be learned using quantitative methodologies instead of a descriptive approach. It was intended for the serious computing professional who wanted a detailed understanding of computers.
A majority of the readers for this book do not plan to become computer architects. The performance and energy efficiency of future software systems will be dramatically affected, however, by how well software designers understand the basic hardware techniques at work in a system. Thus, compiler writers, operating system designers, database programmers, and most other software engineers need a firm grounding in the principles presented in this book. Similarly, hardware designers must understand clearly the effects of their work on software applications.
Thus, we knew that this book had to be much more than a subset of the material in Computer Architecture, and the material was extensively revised to match the different audience. We were so happy with the result that the subsequent editions of Computer Architecture were revised to remove most of the introductory material; hence, there is much less overlap today than with the first editions of both books.
Some readers may be familiar with Computer Architecture: A Quantitative Approach, popularly known as Hennessy and Patterson. (This book in turn is often called Patterson and Hennessy.) Our motivation in writing the earlier book was to describe the principles of computer architecture using solid engineering fundamentals and quantitative cost/performance tradeoffs. We used an approach that combined examples and measurements, based on commercial systems, to create realistic design experiences. Our goal was to demonstrate that computer architecture could be learned using quantitative methodologies instead of a descriptive approach. It was intended for the serious computing professional who wanted a detailed understanding of computers.
A majority of the readers for this book do not plan to become computer architects. The performance and energy efficiency of future software systems will be dramatically affected, however, by how well software designers understand the basic hardware techniques at work in a system. Thus, compiler writers, operating system designers, database programmers, and most other software engineers need a firm grounding in the principles presented in this book. Similarly, hardware designers must understand clearly the effects of their work on software applications.
Thus, we knew that this book had to be much more than a subset of the material in Computer Architecture, and the material was extensively revised to match the different audience. We were so happy with the result that the subsequent editions of Computer Architecture were revised to remove most of the introductory material; hence, there is much less overlap today than with the first editions of both books.
There's a new edition coming out next year, and I think this edition is already outdated, the most recent one is the 6th edition from 2017.
I wonder if the 7th edition will cover the Mill CPU. It should but I doubt it will.
https://millcomputing.com
https://millcomputing.com
This is a book about actual microprocessors you can tape out or buy.
That project seems pretty much dead, running on fumes. A message from mid-2024 after a year of silence:
>At this point all of the areas we are working on could progress much faster with money for hiring people. That was not always the case…
>Also, we could disclose a lot more if we could file patents for what we still have as internal ideas, but that requires money as well.
And in 2020:
>In some ways the plague [COVID] is much less a problem for the Mill project than for other businesses. We have always been a distributed virtual company, so we already had work-from-home worked out. And as a sweat-equity organization with a burn rate of zero we have an infinite runway, while so many others are shut down and going bust.
At some point (now), you have to give up on the hope for a white knight to show up and fund you, and just go the H&P way and publish what you are working on. No one will steal your inventions.
>At this point all of the areas we are working on could progress much faster with money for hiring people. That was not always the case…
>Also, we could disclose a lot more if we could file patents for what we still have as internal ideas, but that requires money as well.
And in 2020:
>In some ways the plague [COVID] is much less a problem for the Mill project than for other businesses. We have always been a distributed virtual company, so we already had work-from-home worked out. And as a sweat-equity organization with a burn rate of zero we have an infinite runway, while so many others are shut down and going bust.
At some point (now), you have to give up on the hope for a white knight to show up and fund you, and just go the H&P way and publish what you are working on. No one will steal your inventions.
I remember when the first edition came out---back in the early 90's!!!! I was young, slim, had a full head of hair---and this new textbook was the bomb. Vastly better than any previous textbook on computer architecture.
I can't believe it is still the best. it's been like 30 years. During that time, so much has happened--the death of supercomputer companies like Convex and Cray, SIMD going from expensive computers like the MASPAR MP-1 to being on virtually every processor, the dot com boom, the rise of google-style server farms, etc etc.
And now the transition to neural net processing.
I mean, it is a testament to the authors that they could keep their competitors from even thinking about trying to write a competing book for so long. It is a great case study in how to stay relevant in tech for the long term.
But man, before it came out, every year 2 or 3 new textbooks in computer architecture came out, each one detailing the next cool thing which computer architectures were being called upon to do.
It's exhibit A of Peter Thiel's case that we are living in an era of very low innovation. If Computer Architecture were a really healthy field, classes would have to be taught from recently-published papers, because it was moving faster than a textbook could be published.
Hat's off to the authors, but man, this is really depressing.
I can't believe it is still the best. it's been like 30 years. During that time, so much has happened--the death of supercomputer companies like Convex and Cray, SIMD going from expensive computers like the MASPAR MP-1 to being on virtually every processor, the dot com boom, the rise of google-style server farms, etc etc.
And now the transition to neural net processing.
I mean, it is a testament to the authors that they could keep their competitors from even thinking about trying to write a competing book for so long. It is a great case study in how to stay relevant in tech for the long term.
But man, before it came out, every year 2 or 3 new textbooks in computer architecture came out, each one detailing the next cool thing which computer architectures were being called upon to do.
It's exhibit A of Peter Thiel's case that we are living in an era of very low innovation. If Computer Architecture were a really healthy field, classes would have to be taught from recently-published papers, because it was moving faster than a textbook could be published.
Hat's off to the authors, but man, this is really depressing.
> If Computer Architecture were a really healthy field, classes would have to be taught from recently-published papers, because it was moving faster than a textbook could be published.
I really don't get this perspective. How can you possibly hope to understand "recently-published papers" without first understanding the basics of the field, which is what Hennessy and Patterson covers? Every subject has introductory textbooks from which introductory courses are taught, and then you can take more advanced courses that can, among other things, include material from recently-published papers. Are there even any fields where courses must be taught from recently-published papers?
On another note, it's not like no more computer architecture textbooks are made. Look at the Synthesis Lectures on Computer Architecture series.
I really don't get this perspective. How can you possibly hope to understand "recently-published papers" without first understanding the basics of the field, which is what Hennessy and Patterson covers? Every subject has introductory textbooks from which introductory courses are taught, and then you can take more advanced courses that can, among other things, include material from recently-published papers. Are there even any fields where courses must be taught from recently-published papers?
On another note, it's not like no more computer architecture textbooks are made. Look at the Synthesis Lectures on Computer Architecture series.
// I really don't get this perspective. How can you possibly hope to understand "recently-published papers" without first understanding the basics of the field, //
A healthy field moves faster than the textbooks can keep up. Consider the field of, say, personal transportation, during the turn of the century. I'm sure they had some very classic textbooks on veterinary medicine for horses and oxen. But they probably didn't have a lot of classic textbooks on being an auto mechanic.
In the 80's and 90's, if you were studying AI in school, they'd be teaching you prolog, first order logic, various parsing techniques, heuristics to search through graphs. Now it is neural nets, transformers, etc.
A healthy field has to "tear up the textbooks" every 10 years or so.
A healthy field moves faster than the textbooks can keep up. Consider the field of, say, personal transportation, during the turn of the century. I'm sure they had some very classic textbooks on veterinary medicine for horses and oxen. But they probably didn't have a lot of classic textbooks on being an auto mechanic.
In the 80's and 90's, if you were studying AI in school, they'd be teaching you prolog, first order logic, various parsing techniques, heuristics to search through graphs. Now it is neural nets, transformers, etc.
A healthy field has to "tear up the textbooks" every 10 years or so.
Vastly? I dunno about that. I was rather fond of Tanenbaum's Structured Computer Organization.
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First edition still has a better cover, but the 7th edition one isn’t… bad.
Plus the first edition was hardcover initially. The 3rd edition seems to be the last hardcover edition.
Is there a 7th edition out? I couldn't find it.
https://www.amazon.com/Computer-Architecture-Quantitative-Ap...
https://shop.elsevier.com/books/computer-architecture/hennes... - If you want paperback + PDF for the same price as just the paperback from Amazon.
https://shop.elsevier.com/books/computer-architecture/hennes... - If you want paperback + PDF for the same price as just the paperback from Amazon.
I just found a preview picture. Other people said “soon” but that’s all I know.
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This is the September 2011 edition to be, uh, quantitative.