Programming Languages
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Lab 7: Floating-Point Addition 0.0
Lab 7: Floating-Point Addition 0.0 Introduction In this lab, you will write a MIPS assembly language function that performs floating-point addition. You will then run your program using PCSpim (just as you did in Lab 6). For testing, you are provided a program that calls your function to compute the value of the mathematical constant e. For those with no assembly language experience, this will be a long lab, so plan your time accordingly. Background You should be familiar with the IEEE 754 Floating-Point Standard, which is described in Section 3.6 of your book. (Hopefully you have read that section carefully!) Here we will be dealing only with single precision floating- point values, which are formatted as follows (this is also described in the “Floating-Point Representation” subsec- tion of Section 3.6 in your book): Sign Exponent (8 bits) Significand (23 bits) 31 30 29 ... 24 23 22 21 ... 0 Remember that the exponent is biased by 127, which means that an exponent of zero is represented by 127 (01111111). The exponent is not encoded using 2s-complement. The significand is always positive, and the sign bit is kept separately. Note that the actual significand is 24 bits long; the first bit is always a 1 and thus does not need to be stored explicitly. This will be important to remember when you write your function! There are several details of IEEE 754 that you will not have to worry about in this lab. For example, the expo- nents 00000000 and 11111111 are reserved for special purposes that are described in your book (representing zero, denormalized numbers and NaNs). -
Bounds Checking on GPU
Noname manuscript No. (will be inserted by the editor) Bounds Checking on GPU Troels Henriksen Received: date / Accepted: date Abstract We present a simple compilation strategy for safety-checking array indexing in high-level languages on GPUs. Our technique does not depend on hardware support for abnormal termination, and is designed to be efficient in the non-failing case. We rely on certain properties of array languages, namely the absence of arbitrary cross-thread communication, to ensure well-defined execution in the presence of failures. We have implemented our technique in the compiler for the functional array language Futhark, and an empirical eval- uation on 19 benchmarks shows that the geometric mean overhead of checking array indexes is respectively 4% and 6% on two different GPUs. Keywords GPU · functional programming · compilers 1 Introduction Programming languages can be divided roughly into two categories: unsafe languages, where programming errors can lead to unpredictable results at run- time; and safe languages, where all risky operations are guarded by run-time checks. Consider array indexing, where an invalid index will lead an unsafe lan- guage to read from an invalid memory address. At best, the operating system will stop the program, but at worst, the program will silently produce invalid results. A safe language will perform bounds checking to verify that the array index is within the bounds of the array, and if not, signal that something is amiss. Some languages perform an abnormal termination of the program and print an error message pointing to the offending program statement. Other languages throw an exception, allowing the problem to be handled by the pro- gram itself. -
The Hexadecimal Number System and Memory Addressing
C5537_App C_1107_03/16/2005 APPENDIX C The Hexadecimal Number System and Memory Addressing nderstanding the number system and the coding system that computers use to U store data and communicate with each other is fundamental to understanding how computers work. Early attempts to invent an electronic computing device met with disappointing results as long as inventors tried to use the decimal number sys- tem, with the digits 0–9. Then John Atanasoff proposed using a coding system that expressed everything in terms of different sequences of only two numerals: one repre- sented by the presence of a charge and one represented by the absence of a charge. The numbering system that can be supported by the expression of only two numerals is called base 2, or binary; it was invented by Ada Lovelace many years before, using the numerals 0 and 1. Under Atanasoff’s design, all numbers and other characters would be converted to this binary number system, and all storage, comparisons, and arithmetic would be done using it. Even today, this is one of the basic principles of computers. Every character or number entered into a computer is first converted into a series of 0s and 1s. Many coding schemes and techniques have been invented to manipulate these 0s and 1s, called bits for binary digits. The most widespread binary coding scheme for microcomputers, which is recog- nized as the microcomputer standard, is called ASCII (American Standard Code for Information Interchange). (Appendix B lists the binary code for the basic 127- character set.) In ASCII, each character is assigned an 8-bit code called a byte. -
POINTER (IN C/C++) What Is a Pointer?
POINTER (IN C/C++) What is a pointer? Variable in a program is something with a name, the value of which can vary. The way the compiler and linker handles this is that it assigns a specific block of memory within the computer to hold the value of that variable. • The left side is the value in memory. • The right side is the address of that memory Dereferencing: • int bar = *foo_ptr; • *foo_ptr = 42; // set foo to 42 which is also effect bar = 42 • To dereference ted, go to memory address of 1776, the value contain in that is 25 which is what we need. Differences between & and * & is the reference operator and can be read as "address of“ * is the dereference operator and can be read as "value pointed by" A variable referenced with & can be dereferenced with *. • Andy = 25; • Ted = &andy; All expressions below are true: • andy == 25 // true • &andy == 1776 // true • ted == 1776 // true • *ted == 25 // true How to declare pointer? • Type + “*” + name of variable. • Example: int * number; • char * c; • • number or c is a variable is called a pointer variable How to use pointer? • int foo; • int *foo_ptr = &foo; • foo_ptr is declared as a pointer to int. We have initialized it to point to foo. • foo occupies some memory. Its location in memory is called its address. &foo is the address of foo Assignment and pointer: • int *foo_pr = 5; // wrong • int foo = 5; • int *foo_pr = &foo; // correct way Change the pointer to the next memory block: • int foo = 5; • int *foo_pr = &foo; • foo_pr ++; Pointer arithmetics • char *mychar; // sizeof 1 byte • short *myshort; // sizeof 2 bytes • long *mylong; // sizeof 4 byts • mychar++; // increase by 1 byte • myshort++; // increase by 2 bytes • mylong++; // increase by 4 bytes Increase pointer is different from increase the dereference • *P++; // unary operation: go to the address of the pointer then increase its address and return a value • (*P)++; // get the value from the address of p then increase the value by 1 Arrays: • int array[] = {45,46,47}; • we can call the first element in the array by saying: *array or array[0]. -
Subtyping Recursive Types
ACM Transactions on Programming Languages and Systems, 15(4), pp. 575-631, 1993. Subtyping Recursive Types Roberto M. Amadio1 Luca Cardelli CNRS-CRIN, Nancy DEC, Systems Research Center Abstract We investigate the interactions of subtyping and recursive types, in a simply typed λ-calculus. The two fundamental questions here are whether two (recursive) types are in the subtype relation, and whether a term has a type. To address the first question, we relate various definitions of type equivalence and subtyping that are induced by a model, an ordering on infinite trees, an algorithm, and a set of type rules. We show soundness and completeness between the rules, the algorithm, and the tree semantics. We also prove soundness and a restricted form of completeness for the model. To address the second question, we show that to every pair of types in the subtype relation we can associate a term whose denotation is the uniquely determined coercion map between the two types. Moreover, we derive an algorithm that, when given a term with implicit coercions, can infer its least type whenever possible. 1This author's work has been supported in part by Digital Equipment Corporation and in part by the Stanford-CNR Collaboration Project. Page 1 Contents 1. Introduction 1.1 Types 1.2 Subtypes 1.3 Equality of Recursive Types 1.4 Subtyping of Recursive Types 1.5 Algorithm outline 1.6 Formal development 2. A Simply Typed λ-calculus with Recursive Types 2.1 Types 2.2 Terms 2.3 Equations 3. Tree Ordering 3.1 Subtyping Non-recursive Types 3.2 Folding and Unfolding 3.3 Tree Expansion 3.4 Finite Approximations 4. -
A Variable Precision Hardware Acceleration for Scientific Computing Andrea Bocco
A variable precision hardware acceleration for scientific computing Andrea Bocco To cite this version: Andrea Bocco. A variable precision hardware acceleration for scientific computing. Discrete Mathe- matics [cs.DM]. Université de Lyon, 2020. English. NNT : 2020LYSEI065. tel-03102749 HAL Id: tel-03102749 https://tel.archives-ouvertes.fr/tel-03102749 Submitted on 7 Jan 2021 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. N°d’ordre NNT : 2020LYSEI065 THÈSE de DOCTORAT DE L’UNIVERSITÉ DE LYON Opérée au sein de : CEA Grenoble Ecole Doctorale InfoMaths EDA N17° 512 (Informatique Mathématique) Spécialité de doctorat :Informatique Soutenue publiquement le 29/07/2020, par : Andrea Bocco A variable precision hardware acceleration for scientific computing Devant le jury composé de : Frédéric Pétrot Président et Rapporteur Professeur des Universités, TIMA, Grenoble, France Marc Dumas Rapporteur Professeur des Universités, École Normale Supérieure de Lyon, France Nathalie Revol Examinatrice Docteure, École Normale Supérieure de Lyon, France Fabrizio Ferrandi Examinateur Professeur associé, Politecnico di Milano, Italie Florent de Dinechin Directeur de thèse Professeur des Universités, INSA Lyon, France Yves Durand Co-directeur de thèse Docteur, CEA Grenoble, France Cette thèse est accessible à l'adresse : http://theses.insa-lyon.fr/publication/2020LYSEI065/these.pdf © [A. -
Cmsc330 Cybersecurity
cmsc330 Cybersecurity Cybersecurity Breaches Major security breaches of computer systems are a fact of life. They affect companies, governments, and individuals. Focusing on breaches of individuals' information, consider just a few examples: Equifax (2017) - 145 million consumers’ records Adobe (2013) - 150 million records, 38 million users eBay (2014) - 145 million records Anthem (2014) - Records of 80 million customers Target (2013) - 110 million records Heartland (2008) - 160 million records Vulnerabilities: Security-relevant Defects The causes of security breaches are varied but many of them, including those given above, owe to a defect (or bug) or design flaw in a targeted computer system's software. The software problem can be exploited by an attacker. An exploit is a particular, cleverly crafted input, or a series of (usually unintuitive) interactions with the system, which trigger the bug or flaw in a way that helps the attacker. Kinds of Vulnerability One obvious sort of vulnerability is a bug in security policy enforcement code. For example, suppose you are implementing an operating system and you have code to enforce access control policies on files. This is the code that makes sure that if Alice's policy says that only she is allowed to edit certain files, then user Bob will not be allowed to modify them. Perhaps your enforcement code failed to consider a corner case, and as a result Bob is able to write those files even though Alice's policy says he shouldn't. This is a vulnerability. A more surprising sort of vulnerability is a bug in code that seems to have nothing to do with enforcing security all. -
CS31 Discussion 1E Spring 17’: Week 08
CS31 Discussion 1E Spring 17’: week 08 TA: Bo-Jhang Ho [email protected] Credit to former TA Chelsea Ju Project 5 - Map cipher to crib } Approach 1: For each pair of positions, check two letters in cipher and crib are both identical or different } For each pair of positions pos1 and pos2, cipher[pos1] == cipher[pos2] should equal to crib[pos1] == crib[pos2] } Approach 2: Get the positions of the letter and compare } For each position pos, indexes1 = getAllPositions(cipher, pos, cipher[pos]) indexes2 = getAllPositions(crib, pos, crib[pos]) indexes1 should equal to indexes2 Project 5 - Map cipher to crib } Approach 3: Generate the mapping } We first have a mapping array char cipher2crib[128] = {‘\0’}; } Then whenever we attempt to map letterA in cipher to letterB in crib, we first check whether it violates the previous setup: } Is cipher2crib[letterA] != ‘\0’? // implies letterA has been used } Then cipher2crib[letterA] should equal to letterB } If no violation happens, } cipher2crib[letterA] = letterB; Road map of CS31 String Array Function Class Variable If / else Loops Pointer!! Cheat sheet Data type } int *a; } a is a variable, whose data type is int * } a stores an address of some integer “Use as verbs” } & - address-of operator } &b means I want to get the memory address of variable b } * - dereference operator } *c means I want to retrieve the value in address c Memory model Address Memory Contents 1000 1 byte 1001 1002 1003 1004 1005 1006 1007 1008 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 Memory model Address Memory -
Safe Arrays Via Regions and Dependent Types
Safe Arrays via Regions and Dependent Types Christian Grothoff1 Jens Palsberg1 Vijay Saraswat2 1 UCLA Computer Science Department University of California, Los Angeles [email protected], [email protected] 2 IBM T.J. Watson Research Center P.O. Box 704, Yorktown Heights, NY 10598, USA [email protected] Abstract. Arrays over regions of points were introduced in ZPL in the late 1990s and later adopted in Titanium and X10 as a means of simpli- fying the programming of high-performance software. A region is a set of points, rather than an interval or a product of intervals, and enables the programmer to write a loop that iterates over a region. While conve- nient, regions do not eliminate the risk of array bounds violations. Until now, language implementations have resorted to checking array accesses dynamically or to warning the programmer that bounds violations lead to undefined behavior. In this paper we show that a type system for a language with arrays over regions can guarantee that array bounds vi- olations cannot occur. We have developed a core language and a type system, proved type soundness, settled the complexity of the key deci- sion problems, implemented an X10 version which embodies the ideas of our core language, written a type checker for our X10 version, and ex- perimented with a variety of benchmark programs. Our type system uses dependent types and enables safety without dynamic bounds checks. 1 Introduction Type-safe languages allow programmers to be more productive by eliminating such difficult-to-find errors as memory corruption. However, type safety comes at a cost in runtime performance due to the need for dynamic safety checks. -
Chapter 9: Memory Management
Chapter 9: Memory Management I Background I Swapping I Contiguous Allocation I Paging I Segmentation I Segmentation with Paging Operating System Concepts 9.1 Silberschatz, Galvin and Gagne 2002 Background I Program must be brought into memory and placed within a process for it to be run. I Input queue – collection of processes on the disk that are waiting to be brought into memory to run the program. I User programs go through several steps before being run. Operating System Concepts 9.2 Silberschatz, Galvin and Gagne 2002 Binding of Instructions and Data to Memory Address binding of instructions and data to memory addresses can happen at three different stages. I Compile time: If memory location known a priori, absolute code can be generated; must recompile code if starting location changes. I Load time: Must generate relocatable code if memory location is not known at compile time. I Execution time: Binding delayed until run time if the process can be moved during its execution from one memory segment to another. Need hardware support for address maps (e.g., base and limit registers). Operating System Concepts 9.3 Silberschatz, Galvin and Gagne 2002 Multistep Processing of a User Program Operating System Concepts 9.4 Silberschatz, Galvin and Gagne 2002 Logical vs. Physical Address Space I The concept of a logical address space that is bound to a separate physical address space is central to proper memory management. ✦ Logical address – generated by the CPU; also referred to as virtual address. ✦ Physical address – address seen by the memory unit. I Logical and physical addresses are the same in compile- time and load-time address-binding schemes; logical (virtual) and physical addresses differ in execution-time address-binding scheme. -
Runtime Defenses 1 Baggy Bounds Checking
Runtime Defenses Nicholas Carlini 7 September, 2011 1 Baggy Bounds Checking 1.1 Motivation There are large amounts of legacy C programs which can not be rewritten entirely. Since memory must be manually managed in C, and bounds are not checked automatically on pointer dereferences, C often contains many memory-saftey bugs. One common type of bug is buffer overflows, where the length of an array is not checked before copying data in to the array: data is written past the end of the array and on top of whatever happens to be at that memory location. 1.2 Baggy Bounds Checking Baggy bounds checking was proposed as a possible defense which would detect when pointers wrote to a memory location out of bounds. It is a runtime defense, which uses source code instrumentation. At a very high level, baggy bounds checking keeps track of bounds information on allocated objects. When a pointer which indexes in to allocated memory is dereferenced, bounds checking code ensures that the pointer still is indexing the same allocated memory location. If the pointer points out of bounds of that object, the program is halted. Baggy bounds checking uses a buddy allocator to return objects of size 2n, and fills the remaining unused bytes with 0s. A bounds table is created containing the log of the sizes of every allocated object. Using this table allows for single-memory-access lookups, which is much more efficient than other methods which require multiple memory accesses. 1.3 Baggy Bounds Checking Failures Baggy bounds checking does not work in all situations, however. -
Spring 2015 CS 161 Computer Security Optional Notes Memory
CS 161 Optional Notes Spring 2015 Computer Security 1 Memory safety | Attacks and Defenses In the first few lectures we will be looking at software security|problems associated with the software implementation. You may have a perfect design, a perfect specification, perfect algorithms, but still have implementation vulnerabilities. In fact, after configuration errors, implementation errors are probably the largest single class of security errors exploited in practice. We will start by looking at a particularly prevalent class of software flaws, those that concern memory safety. Memory safety refers to ensuring the integrity of a program's data structures: preventing attackers from reading or writing to memory locations other than those intended by the programmer. Because many security-critical applications have been written in C, and because C has peculiar pitfalls of its own, many of these examples will be C-specific. Implementation flaws can in fact occur at all levels: in improper use of the programming language, the libraries, the operating system, or in the application logic. We will look at some of these others later in the course. 1 Buffer overflow vulnerabilities We'll start with one of the most common types of error|buffer overflow (also called buffer overrun) vulnerabilities. Buffer overflow vulnerabilities are a particular risk in C. Since it is an especially widely used systems programming language, you might not be surprised to hear that buffer overflows are one of the most pervasive kind of implementation flaws around. As a low-level language, we can think of C as a portable assembly language. The programmer is exposed to the bare machine (which is one reason that C is such a popular systems language).