The document discusses register allocation techniques in LLVM. It introduces the register allocation problem and describes LLVM's template method for register allocation. It then discusses LLVM's basic greedy register allocation approach, which prioritizes assigning registers to live intervals with higher spill costs. Finally, it describes LLVM's greedy register allocation in more detail, including techniques for live interval splitting such as local, instruction, region and block splitting using algorithms like Hopfield networks.
The Linux Block Layer - Built for Fast StorageKernel TLV
The arrival of flash storage introduced a radical change in performance profiles of direct attached devices. At the time, it was obvious that Linux I/O stack needed to be redesigned in order to support devices capable of millions of IOPs, and with extremely low latency.
In this talk we revisit the changes the Linux block layer in the
last decade or so, that made it what it is today - a performant, scalable, robust and NUMA-aware subsystem. In addition, we cover the new NVMe over Fabrics support in Linux.
Sagi Grimberg
Sagi is Principal Architect and co-founder at LightBits Labs.
Debug Information And Where They Come FromMin-Yih Hsu
(Presented in COSCUP 2022)
Debug information is a mapping between the original source code and low-level binary locations. It provides developers powerful insights to diagnose problems (via debuggers) in their code and acts as one of the most important foundations for modern software development. Furthermore, in recent years, we are seeing increasing demands of high quality debug information for highly optimized applications that are otherwise “un-debuggable”. For instance, debugging unoptimized games is generally not feasible since it’s likely to miss every single frame. In this talk, we are going to introduce how debug information works and how compilers generate proper debug info even with extensive levels of optimization enabled. At the end of this talk, you will gain insights into the structure of debug information and learn key compiler engineering knowledge on generating high quality debug info for critical, highly optimized software.
The slides begins with introduction to the character drivers and then mentions the various APIs for registering the character driver. Dynamically creating the device file and IOCTL
BUD17-302: LLVM Internals #2
Speaker: Renato Golin, Peter Smith, Diana Picus, Omair Javaid, Adhemerval Zanella
Track: Toolchain
★ Session Summary ★
Continuing from LAS16 and, if we have time, introducing global isel that we’re working on.
---------------------------------------------------
★ Resources ★
Event Page: http://connect.linaro.org/resource/bud17/bud17-302/
Presentation:
Video:
---------------------------------------------------
★ Event Details ★
Linaro Connect Budapest 2017 (BUD17)
6-10 March 2017
Corinthia Hotel, Budapest,
Erzsébet krt. 43-49,
1073 Hungary
---------------------------------------------------
http://www.linaro.org
http://connect.linaro.org
---------------------------------------------------
Follow us on Social Media
https://www.facebook.com/LinaroOrg
https://twitter.com/linaroorg
https://www.youtube.com/user/linaroorg?sub_confirmation=1
https://www.linkedin.com/company/1026961
"
Introduce Brainf*ck, another Turing complete programming language. Then, try to implement the following from scratch: Interpreter, Compiler [x86_64 and ARM], and JIT Compiler.
Note: When you view the the slide deck via web browser, the screenshots may be blurred. You can download and view them offline (Screenshots are clear).
The Linux Block Layer - Built for Fast StorageKernel TLV
The arrival of flash storage introduced a radical change in performance profiles of direct attached devices. At the time, it was obvious that Linux I/O stack needed to be redesigned in order to support devices capable of millions of IOPs, and with extremely low latency.
In this talk we revisit the changes the Linux block layer in the
last decade or so, that made it what it is today - a performant, scalable, robust and NUMA-aware subsystem. In addition, we cover the new NVMe over Fabrics support in Linux.
Sagi Grimberg
Sagi is Principal Architect and co-founder at LightBits Labs.
Debug Information And Where They Come FromMin-Yih Hsu
(Presented in COSCUP 2022)
Debug information is a mapping between the original source code and low-level binary locations. It provides developers powerful insights to diagnose problems (via debuggers) in their code and acts as one of the most important foundations for modern software development. Furthermore, in recent years, we are seeing increasing demands of high quality debug information for highly optimized applications that are otherwise “un-debuggable”. For instance, debugging unoptimized games is generally not feasible since it’s likely to miss every single frame. In this talk, we are going to introduce how debug information works and how compilers generate proper debug info even with extensive levels of optimization enabled. At the end of this talk, you will gain insights into the structure of debug information and learn key compiler engineering knowledge on generating high quality debug info for critical, highly optimized software.
The slides begins with introduction to the character drivers and then mentions the various APIs for registering the character driver. Dynamically creating the device file and IOCTL
BUD17-302: LLVM Internals #2
Speaker: Renato Golin, Peter Smith, Diana Picus, Omair Javaid, Adhemerval Zanella
Track: Toolchain
★ Session Summary ★
Continuing from LAS16 and, if we have time, introducing global isel that we’re working on.
---------------------------------------------------
★ Resources ★
Event Page: http://connect.linaro.org/resource/bud17/bud17-302/
Presentation:
Video:
---------------------------------------------------
★ Event Details ★
Linaro Connect Budapest 2017 (BUD17)
6-10 March 2017
Corinthia Hotel, Budapest,
Erzsébet krt. 43-49,
1073 Hungary
---------------------------------------------------
http://www.linaro.org
http://connect.linaro.org
---------------------------------------------------
Follow us on Social Media
https://www.facebook.com/LinaroOrg
https://twitter.com/linaroorg
https://www.youtube.com/user/linaroorg?sub_confirmation=1
https://www.linkedin.com/company/1026961
"
Introduce Brainf*ck, another Turing complete programming language. Then, try to implement the following from scratch: Interpreter, Compiler [x86_64 and ARM], and JIT Compiler.
Note: When you view the the slide deck via web browser, the screenshots may be blurred. You can download and view them offline (Screenshots are clear).
A quick tutorial on what debuggers are and how to use them. We present a debugging example using GDB. At the end of this tutorial, you will be able to work your way through a crash and analyze the cause of the error responsible for the crash.
Inside Cassandra – C* is an interesting piece of software for many reasons, but it is especially interesting in its use of elegant data structures and algorithms. This talk will focus on the data structures and algorithms that make C* such a scalable and performant database. We will walk along the write, read and delete paths exploring the low-level details of how each of these operations work. We will also explore some of the background processes that maintain availability and performance. The goal of this talk is to gain a deeper understanding of C* by exploring the low-level details of its implementation.
"HHVM is a high-performance, open source PHP execution engine developed at Facebook. It’s the fastest PHP runtime in the world, with support for PHP5, PHP7, and Hack—the programming language used for Facebook’s web server application logic. In addition to powering Facebook’s web tier, HHVM has also been adopted by other major services such as Wikipedia, Baidu, and Box.
HHVM uses just-in-time compilation to transform PHP and Hack source code into optimized machine code. Thanks to contributions from developers across the ARM community, HHVM can now target AArch64 in addition to x86-64 and successfully runs open source PHP frameworks like WordPress. Join us for an overview of HHVM, a quick demo, and some thoughts on where optimization efforts can go from here."
Good news, everybody! Guile 2.2 performance notes (FOSDEM 2016)Igalia
By Andy Wingo.
With the new compiler and virtual machine in Guile 2.2, Guile hackers need to update their mental performance models. This talk will give a bit of a state of the union of Guile performance, with an updated overview of the cost of various kinds of abstractions. Sometimes abstraction is free!
(c) 2016 FOSDEM VZW
CC BY 2.0 BE
https://archive.fosdem.org/2016/
Slides from JEEConf 2018 talk "Virtual Machine for Regular Expressions". It describes how and why to implement a custom regular expression engine for matching arbitrary sequences.
MuVM: Higher Order Mutation Analysis Virtual Machine for CSusumu Tokumoto
Mutation analysis is a method for evaluating the effectiveness of a test suite by seeding faults artificially and measuring the fraction of seeded faults detected by the test suite. The major limitation of mutation analysis is its lengthy execution time because it involves generating, compiling and running large numbers of mutated programs, called mutants. Our tool MuVM achieves a significant runtime improvement by performing higher order mutation analysis using four techniques, metamutation, mutation on virtual machine, higher order split-stream execution, and online adaptation technique. In order to obtain the same behavior as mutating the source code directly, metamutation preserves the mutation location information which may potentially be lost during bitcode compilation and optimization. Mutation on a virtual machine reduces the compilation and testing cost by compiling a program once and invoking a process once. Higher order split-stream execution also reduces the testing cost by executing common parts of the mutants together and splitting the execution at a seeded fault. Online adaptation technique reduces the number of generated mutants by omitting infeasible mutants. Our comparative experiments indicate that our tool is significantly superior to an existing tool, an existing technique (mutation schema generation), and no-split-stream execution in higher order mutation.
Lecture slides that I used in Advanced Information Security Summer School (AIS3, 2016 & 2018) in Taiwan. https://ais3.org/
台湾の高度セキュリティ人材育成プログラム(AIS3, 2016/2018)の講義で利用した講義資料です。
OpenFOAM solver for Helmholtz equation, helmholtzFoam / helmholtzBubbleFoamtakuyayamamoto1800
In this slide, we show the simulation example and the way to compile this solver.
In this solver, the Helmholtz equation can be solved by helmholtzFoam. Also, the Helmholtz equation with uniformly dispersed bubbles can be simulated by helmholtzBubbleFoam.
Enterprise Resource Planning System includes various modules that reduce any business's workload. Additionally, it organizes the workflows, which drives towards enhancing productivity. Here are a detailed explanation of the ERP modules. Going through the points will help you understand how the software is changing the work dynamics.
To know more details here: https://blogs.nyggs.com/nyggs/enterprise-resource-planning-erp-system-modules/
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
May Marketo Masterclass, London MUG May 22 2024.pdfAdele Miller
Can't make Adobe Summit in Vegas? No sweat because the EMEA Marketo Engage Champions are coming to London to share their Summit sessions, insights and more!
This is a MUG with a twist you don't want to miss.
Exploring Innovations in Data Repository Solutions - Insights from the U.S. G...Globus
The U.S. Geological Survey (USGS) has made substantial investments in meeting evolving scientific, technical, and policy driven demands on storing, managing, and delivering data. As these demands continue to grow in complexity and scale, the USGS must continue to explore innovative solutions to improve its management, curation, sharing, delivering, and preservation approaches for large-scale research data. Supporting these needs, the USGS has partnered with the University of Chicago-Globus to research and develop advanced repository components and workflows leveraging its current investment in Globus. The primary outcome of this partnership includes the development of a prototype enterprise repository, driven by USGS Data Release requirements, through exploration and implementation of the entire suite of the Globus platform offerings, including Globus Flow, Globus Auth, Globus Transfer, and Globus Search. This presentation will provide insights into this research partnership, introduce the unique requirements and challenges being addressed and provide relevant project progress.
Launch Your Streaming Platforms in MinutesRoshan Dwivedi
The claim of launching a streaming platform in minutes might be a bit of an exaggeration, but there are services that can significantly streamline the process. Here's a breakdown:
Pros of Speedy Streaming Platform Launch Services:
No coding required: These services often use drag-and-drop interfaces or pre-built templates, eliminating the need for programming knowledge.
Faster setup: Compared to building from scratch, these platforms can get you up and running much quicker.
All-in-one solutions: Many services offer features like content management systems (CMS), video players, and monetization tools, reducing the need for multiple integrations.
Things to Consider:
Limited customization: These platforms may offer less flexibility in design and functionality compared to custom-built solutions.
Scalability: As your audience grows, you might need to upgrade to a more robust platform or encounter limitations with the "quick launch" option.
Features: Carefully evaluate which features are included and if they meet your specific needs (e.g., live streaming, subscription options).
Examples of Services for Launching Streaming Platforms:
Muvi [muvi com]
Uscreen [usencreen tv]
Alternatives to Consider:
Existing Streaming platforms: Platforms like YouTube or Twitch might be suitable for basic streaming needs, though monetization options might be limited.
Custom Development: While more time-consuming, custom development offers the most control and flexibility for your platform.
Overall, launching a streaming platform in minutes might not be entirely realistic, but these services can significantly speed up the process compared to building from scratch. Carefully consider your needs and budget when choosing the best option for you.
Innovating Inference - Remote Triggering of Large Language Models on HPC Clus...Globus
Large Language Models (LLMs) are currently the center of attention in the tech world, particularly for their potential to advance research. In this presentation, we'll explore a straightforward and effective method for quickly initiating inference runs on supercomputers using the vLLM tool with Globus Compute, specifically on the Polaris system at ALCF. We'll begin by briefly discussing the popularity and applications of LLMs in various fields. Following this, we will introduce the vLLM tool, and explain how it integrates with Globus Compute to efficiently manage LLM operations on Polaris. Attendees will learn the practical aspects of setting up and remotely triggering LLMs from local machines, focusing on ease of use and efficiency. This talk is ideal for researchers and practitioners looking to leverage the power of LLMs in their work, offering a clear guide to harnessing supercomputing resources for quick and effective LLM inference.
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I ...Juraj Vysvader
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I didn't get rich from it but it did have 63K downloads (powered possible tens of thousands of websites).
Understanding Globus Data Transfers with NetSageGlobus
NetSage is an open privacy-aware network measurement, analysis, and visualization service designed to help end-users visualize and reason about large data transfers. NetSage traditionally has used a combination of passive measurements, including SNMP and flow data, as well as active measurements, mainly perfSONAR, to provide longitudinal network performance data visualization. It has been deployed by dozens of networks world wide, and is supported domestically by the Engagement and Performance Operations Center (EPOC), NSF #2328479. We have recently expanded the NetSage data sources to include logs for Globus data transfers, following the same privacy-preserving approach as for Flow data. Using the logs for the Texas Advanced Computing Center (TACC) as an example, this talk will walk through several different example use cases that NetSage can answer, including: Who is using Globus to share data with my institution, and what kind of performance are they able to achieve? How many transfers has Globus supported for us? Which sites are we sharing the most data with, and how is that changing over time? How is my site using Globus to move data internally, and what kind of performance do we see for those transfers? What percentage of data transfers at my institution used Globus, and how did the overall data transfer performance compare to the Globus users?
Unleash Unlimited Potential with One-Time Purchase
BoxLang is more than just a language; it's a community. By choosing a Visionary License, you're not just investing in your success, you're actively contributing to the ongoing development and support of BoxLang.
Cyaniclab : Software Development Agency Portfolio.pdfCyanic lab
CyanicLab, an offshore custom software development company based in Sweden,India, Finland, is your go-to partner for startup development and innovative web design solutions. Our expert team specializes in crafting cutting-edge software tailored to meet the unique needs of startups and established enterprises alike. From conceptualization to execution, we offer comprehensive services including web and mobile app development, UI/UX design, and ongoing software maintenance. Ready to elevate your business? Contact CyanicLab today and let us propel your vision to success with our top-notch IT solutions.
Gamify Your Mind; The Secret Sauce to Delivering Success, Continuously Improv...Shahin Sheidaei
Games are powerful teaching tools, fostering hands-on engagement and fun. But they require careful consideration to succeed. Join me to explore factors in running and selecting games, ensuring they serve as effective teaching tools. Learn to maintain focus on learning objectives while playing, and how to measure the ROI of gaming in education. Discover strategies for pitching gaming to leadership. This session offers insights, tips, and examples for coaches, team leads, and enterprise leaders seeking to teach from simple to complex concepts.
Prosigns: Transforming Business with Tailored Technology SolutionsProsigns
Unlocking Business Potential: Tailored Technology Solutions by Prosigns
Discover how Prosigns, a leading technology solutions provider, partners with businesses to drive innovation and success. Our presentation showcases our comprehensive range of services, including custom software development, web and mobile app development, AI & ML solutions, blockchain integration, DevOps services, and Microsoft Dynamics 365 support.
Custom Software Development: Prosigns specializes in creating bespoke software solutions that cater to your unique business needs. Our team of experts works closely with you to understand your requirements and deliver tailor-made software that enhances efficiency and drives growth.
Web and Mobile App Development: From responsive websites to intuitive mobile applications, Prosigns develops cutting-edge solutions that engage users and deliver seamless experiences across devices.
AI & ML Solutions: Harnessing the power of Artificial Intelligence and Machine Learning, Prosigns provides smart solutions that automate processes, provide valuable insights, and drive informed decision-making.
Blockchain Integration: Prosigns offers comprehensive blockchain solutions, including development, integration, and consulting services, enabling businesses to leverage blockchain technology for enhanced security, transparency, and efficiency.
DevOps Services: Prosigns' DevOps services streamline development and operations processes, ensuring faster and more reliable software delivery through automation and continuous integration.
Microsoft Dynamics 365 Support: Prosigns provides comprehensive support and maintenance services for Microsoft Dynamics 365, ensuring your system is always up-to-date, secure, and running smoothly.
Learn how our collaborative approach and dedication to excellence help businesses achieve their goals and stay ahead in today's digital landscape. From concept to deployment, Prosigns is your trusted partner for transforming ideas into reality and unlocking the full potential of your business.
Join us on a journey of innovation and growth. Let's partner for success with Prosigns.
Code reviews are vital for ensuring good code quality. They serve as one of our last lines of defense against bugs and subpar code reaching production.
Yet, they often turn into annoying tasks riddled with frustration, hostility, unclear feedback and lack of standards. How can we improve this crucial process?
In this session we will cover:
- The Art of Effective Code Reviews
- Streamlining the Review Process
- Elevating Reviews with Automated Tools
By the end of this presentation, you'll have the knowledge on how to organize and improve your code review proces
Enhancing Research Orchestration Capabilities at ORNL.pdfGlobus
Cross-facility research orchestration comes with ever-changing constraints regarding the availability and suitability of various compute and data resources. In short, a flexible data and processing fabric is needed to enable the dynamic redirection of data and compute tasks throughout the lifecycle of an experiment. In this talk, we illustrate how we easily leveraged Globus services to instrument the ACE research testbed at the Oak Ridge Leadership Computing Facility with flexible data and task orchestration capabilities.
3. Introduction to Register
Allocation
• Definition
• Register allocation is the problem of mapping
program variables to either machine registers or
memory addresses.
• Best solution
• minimise the number of loads/stores from/to memory
• NP-complete
4. int main()
{
int i, j;
int answer;
for (i = 1; i < 10; i++)
for (j = 1; j < 10; j++) {
answer = i * j;
}
return 0;
}
_main:
@ BB#0:
sub sp, #16
movs r0, #0
str r0, [sp, #12]
movs r0, #1
str r0, [sp, #8]
b LBB0_2
LBB0_1:
adds r1, #1
str r1, [sp, #8]
LBB0_2:
ldr r1, [sp, #8]
cmp r1, #9
bgt LBB0_6
@ BB#3:
str r0, [sp, #4]
b LBB0_5
LBB0_4:
ldr r2, [sp, #4]
muls r1, r2, r1
str r1, [sp]
ldr r1, [sp, #4]
adds r1, #1
5. Graph Coloring
• For an arbitrary graph G; a coloring of G assigns a
color to each node in G so that no pair of adjacent
nodes have the same color.
2-colorable 3-colorable
6. Graph Coloring for RA
• Node: Live interval
• Edge: Two live intervals have interference
• Color: Physical register
• Find a optimal colouring for the graph
9. LLVM Register Allocation
• Basic
• Provide a minimal implementation of the basic register allocator
• Greedy
• Global live range splitting.
• Fast
• This register allocator allocates registers to a basic block at a
time.
• PBQP
• Partitioned Boolean Quadratic Programming (PBQP) based
register allocator for LLVM
10. Template Method
• Define the skeleton of an algorithm in an operation,
deferring some steps to subclasses.
11. LLVM Register Allocation Template Method
Enqueue All
LiveInterval
selectOrSplit for One
LiveInterval
Assign the Physical
Register
Enqueue Split
LiveInterval
dequeue
physical register is available
split live interval
allocatePhysRegs
enqueue
seedLiveRegs
Q
customised by new RA algorithm
for (unsigned i = 0, e = MRI->getNumVirtRegs(); i != e; ++i) {
unsigned Reg = TargetRegisterInfo::index2VirtReg(i);
if (MRI->reg_nodbg_empty(Reg))
continue;
enqueue(&LIS->getInterval(Reg));
}
13. LLVM Basic Register Allocation
Calculate
LiveInterval Weight
Enqueue All
LiveInterval
RABasic::selectOrSplit
Assign the Physical
Register
Enqueue Split
LiveInterval
dequeue
physical register is available
split live interval
update LiveInterval.weight
(spill cost)
allocatePhysRegs
enqueue
seedLiveRegs
priority Q
(spill cost)
customised by RABasic algorithm
struct CompSpillWeight {
bool operator()(LiveInterval *A, LiveInterval *B) const {
return A->weight < B->weight;
}
};
1. Assign physical registers to Live Interval with highest spill cost.
2. If there is no physical registers for current Live Interval, select
the highest spill cost Live Interval between current one and
interferences to assign physical registers.
3. Spill the unassigned Live Intervals.
14. LiveInterval Weight
• Weight for one instruction with the register
• weight = (isDef + isUse) * (Block Frequency / Entry Frequency)
• loop induction variable: weight *= 3
• For all instructions with the register
• totalWeight += weight
• Hint: totalWeight *= 1.01
• Re-materializable: totalWeight *= 0.5
• LiveInterval.weight = totalWeight / size of LiveInterval
22. Greedy RA Stages
• RS_New: created
• RS_Assign: enqueue
• RS_Split: need to split
• RS_Split2
• used for split products that may not be making progress
• RS_Spill: need to spill
• RS_Done: assigned a physical register or created by spill
23. RS_Split2
• The live intervals created by split will enqueue to
process again.
• There is a risk of creating infinite loops.
… = vreg1 …
… = vreg1 …
… = vreg1 …
vreg2 = COPY vreg1
… = vreg2 …
vreg3 = COPY vreg1
… = vreg3 …
… = vreg3 …
RS_New
RS_Split2
24. Greedy Register Allocation
try to assign physical register
try to evict to find better register
enter RS_Split
stage
try last chance
recoloring
split
spill
pick a physical register and evict all
interference
found
register
stage >= RS_Done or
Live Interval is unspillable
stage < RS_Split
selectOrSplit(d+1)
selectOrSplit(d)
stage is RS_Split
or RS_Split2
25. Last Chance Recoloring
• Try to assign a physical register to Live Interval by
evicting all its interferences.
• The recoloring process may recursively use the
last chance recoloring. Therefore, when a virtual
register has been assigned a color by this
mechanism, it is marked as Fixed.
vA can use {R1, R2 }
vB can use { R2, R3}
vC can use {R1 }
vA => R1
vB => R2
vC => fails
vA => R2
vB => R3
vC => R1 (fixed)
selectOrSplit(d) selectOrSplit(d + 1)
26. How to Split?
is stage
beyond
RS_Spill?
is in one BB? tryLocalSplit
tryInstructionSplit
No
Yes
tryRegionSplit
is stage less
than RS_Split2?
No
spill
Yes
success?
No
success?
spill
No
tryBlockSplit
Yes
No
success?
No
success?
spill
No
done
Yes
Yes
done
Yes
Yes
27. tryLocalSplit
• Try to split virtual register interval into smaller
intervals inside its only basic block.
• calculate gap weights
• adjust the split region
35. tryRegionSplit
1. For every physical register, construct Hopfield Network
• Initialize border constraints
• Initialize Hopfield Network nodes according to
border constraints
• Add links to Hopfield Network and iterate
2. Get the best candidate
3. Do region split
46. Initialize Hopfield Network Node
• update BiasN, BiasP according to BorderConstraint
BB #n (freq)
… = Y op …
PrefReg
PrefSpill
Bundle ib
BiasP += freq
Bundle ob
BiasN += freq
void addBias(BlockFrequency freq, BorderConstraint direction) {
switch (direction) {
default:
break;
case PrefReg:
BiasP += freq;
break;
case PrefSpill:
BiasN += freq;
break;
case MustSpill:
BiasN = BlockFrequency::getMaxFrequency(); // (uint64_t)-1ULL
break;
}
}
47. Add Links to Hopfield Network
• add weight to links
Live Through
BB #n (freq)
Bundle ib
Bundle ob
void addLink(unsigned b, BlockFrequency w) {
// Update cached sum.
SumLinkWeights += w;
// There can be multiple links to the same bundle, add them up.
for (LinkVector::iterator I = Links.begin(), E = Links.end(); I !=
if (I->second == b) {
I->first += w;
return;
}
// This must be the first link to b.
Links.push_back(std::make_pair(w, b));
}
(freq, ob)
(freq, ib)
48. Update Hopfield Network
Bundle X
BiasN
BiasP
Value = 0
Bundle A
Value = -1
Bundle B
Value = 1
Bundle C
Value = 1
Bundle D
Value = 1
SumN = BiasN + freqA
SunP = BiasP + freqB + freqC + freqD
(freqA, A) (freqB, B) (freqC, C) (freqD, D)
if (SumN >= SumP + Threshold)
Value = -1;
else if (SumP >= SumN + Threshold)
Value = 1;
else
Value = 0;
a(t)s⇥1 =
⇢
ps⇥1 : t = 0
S(Ws⇥s ⇥ a(t 1)s⇥1 + bs⇥1) : t 1
2
6
6
6
6
4
· · ·
· · ·
· · ·
· · ·
FA FB FC FD 0
3
7
7
7
7
5
⇥
2
6
6
6
6
4
1
1
1
1
0
3
7
7
7
7
5
+
2
6
6
6
6
6
4
...
Biasp Biasn
3
7
7
7
7
7
5
50. splitLiveThroughBlock
Bundle ib
Value == 1
Bundle ob
Value != 1
Live Through
LiveOut on Stack
first non-PHI
Start
New Int
Bundle ib
Value != 1
Bundle ob
Value == 1
Live Through
LiveIn on Stack
last split point
End
New Int
Live Through
No Interference
Bundle ib
Value == 1
Bundle ob
Value == 1
End
New Int
Start
51. splitLiveThroughBlock
Bundle ib
Value == 1
Bundle ob
Value == 1
LiveThrough
Non-overlapping interference
New Int
Interference.first()
Interference.last()
New Int
Bundle ib
Value == 1
Bundle ob
Value == 1
LiveThrough
Overlapping interference
New Int
Interference.first()
Interference.last()
New Int
52. splitRegInBlock
Bundle ib
Value == 1
No LiveOut
Interference after kill
Start
New Int
Bundle ib
Value == 1
Bundle ob
Value != 1
LiveOut on Stack
Interference after last use
LiveOut on Stack
Interference after last use
Interference.fist()
LastInstr
LastInstr
last split point
New Int
Start
Bundle ib
Value == 1
Bundle ob
Value != 1
LastInstr
last split point
New Int
Start
Interference.fist()
Interference.fist()
53. splitRegInBlock
Bundle ib
Value == 1
LiveOut on Stack
Interference overlapping uses
Start
New Int
Bundle ib
Value == 1
Interference.fist()
LastInstr
last split point
New Int
Start
New Int
Interference.fist()
LastInstr
last split point
New Int
Bundle ob
Value != 1
Bundle ob
Value != 1
LiveOut on Stack
Interference overlapping uses
54. splitRegOutBlock
No LiveIn
Interference before def
End
New Int
Bundle ib
Value != 1
Bundle ob
Value == 1
Live Through
Interference before def
Live Through
Interference overlapping uses
Interference.last()
FirstInstr
Bundle ib
Value != 1
Bundle ob
Value == 1
Bundle ob
Value == 1
End
New Int
Interference.last()
FirstInstr
last split point
End
New Int
Interference.last()
FirstInstr
New Int