Schedule C Template Form: Fill & Download for Free

Am I allowed the same amount of time to develop both versions?Will the program specification change during the development period?Just how aggressive is that schedule, anyway?Let’s say I take an isolated function up to a certain size. Now I give it to the world’s best C coder and the world’s best assembly coder, and tell them both: Make it as fast as possible.Given enough time, the assembly coder would almost certainly beat the C coder. At worst, it’d be a tie. That’s especially true if I held the target system fixed—a particular CPU at a particular clock rate, with a particular cache organization, etc. That way, there’s one set of “best” tradeoffs.Now suppose I gave those same two programmers the task of implementing a complex system, with real world time-to-market schedule pressures, and long term maintenance to consider. Oh, and it has to run on a wide range of systems. They might even have different instruction sets—think x86 vs. x86–64 vs. AArch32 vs. AArch64, for example. (AArch32/64 are the 32 vs. 64 bit variants of ARMv8.)It’s not so clear who would win that one, now is it? Actually, I think it is pretty clear: My money’s on the C programmer, by a mile.And if an expert C++ programmer shows up, my money’s on that person. Why?C makes it easier to user higher levels of abstraction in your code, and at least encourages some amount of structured programming. C code tends to be quite a bit more readable than assembly as well. And macros, for all their ugliness, do at least provide some generic programming facilities. You can get things done, and then go back and tune the hotspots. Your code can remain relatively maintainable along the way.C++ makes it much easier to write generic, maintainable code that gets specialized at compile time. It’s free to pull the optimizations you decided were too ugly in C and made the code an unreadable holy mess in assembly. That’s what C++’s expressiveness can do for you.For example, I developed a set of templates and classes that were designed to enable generating machine code at run time. (This was a dynamic code generator used for generating complex cache test cases at run time.) These C++ templates in many cases compiled down to 2 or 3 instructions for every instruction generated, because it was able to migrate most of the opcode generation to compile time. The resulting code generator ran blindingly fast.I can’t imagine trying to write anything nearly so fast in raw assembly code. That’s especially true for an exposed pipeline VLIW, which is what I was coding this for. And I certainly couldn’t have done it in the tight schedule demanded by chip creation and verification. If someone told me to do it in assembly rather than C++, I’d probably have looked for other work. I say that as someone who prides himself in his assembly optimization skills.So back to the original question: Is it possible? If you give real-world constraints, it’s not only possible, but actually damn likely.

To start you off: you may want to pay attention to your terminology. Most people won't be as pedantic about this, but high-performance often relates to high throughput or amount of work completed. Latency and throughput might appear to be positively correlated concepts, but they're literally fighting each other in the computing world. Processor scheduling is typically worked out by balancing the latency versus throughput trade-off (though keep in mind they're technically orthogonal concepts).Why's the above important to your question? You need to understand the problem before the solution. The difference between the two terms are pretty much the foundation of building low-latency systems. To improve throughput, you want your processors to run as fast as possible. This means they just want to keep on running as fast as they can (minimize context switching and optimizing for cache). Low-latency means that the process needs to always be ready to process input (while potentially sacrificing actual work completed - or throughput).Assuming your question is referring to HFT, the above should help shed some light on the problem you're trying to solve with C and C++: to minimize I/O latency - that is, you want to produce an output (order execution) as quickly as the input (market data) comes. So here are some fun ways to speed up I/O starting from your system to C and C++:1. Minimize latency on your network (I know this isn't C or C++, but it's coming). Typically, network latency is one of the most major bottlenecks. You need to grab the shortest network cable with the highest bandwidth on the fastest network card (10-Gs typically).2. Remove data copies and context switches (basically keep off the kernel). The cards mentioned above should support kernel bypassing to allow packets to skip kernel processing. (I promise the C and C++ parts are coming)3. Once you receive this data, you want to optimize the kernel scheduler to place a priority on always doing the I/O over processor (Completely Fair Scheduler might be too general of a scheduler in specialized HFT cases).4. Finally, C and C++: once you get the input, you want to do as little work as possible at run-time. How's that done? In C, macros/pre-processor directives. In C++, template metaprogramming is common. Prefer CRTP over dynamic polymorphism whenever possible. Avoid function pointers unless you're working them through templates to maximize inlining. Use expression templates to build your structures for computation whenever possible.5. Avoid any memory allocations whenever possible. There should be a very limited number of allocations. If anything, learn to use arenas/memory pools with placement new. This avoids the overhead of having to allocate memory without needing to rewrite malloc yourself. Avoid shared_ptrs unless you absolutely need them. The reference counter can cause a lot of latency if not used extremely carefully.6. Prefer undefined behavior over safety where appropriate. Safety checks can be very expensive when you're pushing into the sub-microsecond level.7. Take advantage of your cache. The difference between the cache levels and memory are orders of magnitudes. You want your program to be cache-ready whenever possible. Prefer contiguous blocks of memory over spread memory (similar to prefer to vectors vs linked lists). This also means prefer vectors over unordered_maps/maps/sets/unordered_sets on small data sets. The hash/binary traversal can very easily surpass the cache access of vectors. This means that O(N) can very often exceed the speed of O(1) or (log N) on small sets. I see people abusing sets and unordered_sets a lot, but many at times, searching a vector linearly is significantly faster than constant or logarithmic time due to the cache.8. Work with an entirely systematic approach. Do not ever assume what most C++ developers assume. One huge one is RVO/NRVO. You don't want your compiler determining when your string (or other object) is copied without you knowing. Disassemble your code and make sure your hypothesis is correct. Be explicit and work with move operations and references whenever you can.9. Take note of struct padding. The difference between swapping the order of a large data type and a small one can be massive. In many cases, the compiler will not optimize this for you. You should always be wary about the order of how you declare your structs/classes. The typical order is large to smallest, but you may also need to keep in mind false sharing if you're working in a multi-threaded environment. Prepare some empty char arrays to buffer out your cache lines if you are.10. Take note of your switch statements. If your cases are very far apart without much pattern, there's a chance it's not going to run through a normal jump table. This means two things: (1.) take note of the order of your case statements and (2.) try to minimize the indices of the cases if at all possible. Don't go around enumerating A = 0, B = 1, C = 20, D = 500, E = 9999 if you can avoid it if you plan on throwing it into a case.11. Avoid branches and table lookups. For example, example, using virtual functions and layers of nested ifs will cause a certain degree of cache misses (and extraneous pipeline clearances).12. Take advantage of compiler builtins like __expected and __prefetch (there's way more to experiment with). Again, these are options normally taken well after your C and C++ code has been optimized. They require tons of benchmarking.13. Know what your compiler and linker is doing - don't just be the typical C++ developer that assumes -O2 will do everything. Know which unsafe optimizations can be used safely in your code, and know which and what O2/O3 optimizations may actually slow down your code. This will require tons of bench marking, but it's important to understand your build library.To summarize, don't assume anything. The above doesn't even get near showing the tip of the iceberg. The only way to know the "tricks" is to learn exactly what's going on. Don't just use streams because they're convenient - learn how they're implemented in your context. This gets easier over time since you get a baseline. If you ever moved from Linux to BSD, for example, you could compare the properties and understand with little to no effort how to optimize your code for the environment.By the way, I tried to cover as much as I could in a reasonable time, so I didn't cite any sources. Please feel free to Google anything up and comment if there's anything that needs explanation or correction. Also, the above is written for those that believe the algorithms used for their systems are already at an optimal state.Edit: Didn't realized I typed this much. I'm going to section this answer.

When you are first starting out you can usually get away with a very simple accounting solution.How simple? I’ve seen businesses under $1m run on spreadsheets. Seriously. And it worked fine for them. I have even seen a Google Sheets template that “encouraged” people to categorize their business expenses to line up with Schedule C account groupings. Then when the owner filed their taxes it made completing the Schedule C part of their return very easy.The next step beyond that is likely Quicken Home & Business. This version of Quicken lets you break apart personal and business expenses very easily. Like the spreadsheet I mentioned above, this option also allows you to assign Schedule C groupings to expenses to make tax filing easier. It also allows for easy running of P&L statements and other reports.Stepping up again in complexity, features, and cost would be Quickbooks. I used Quickbooks for 18 years running my tech company. It worked perfectly for our needs - which honestly were fairly complex with everything we had going on.Zero, Freshbooks, and Wave are others comparable to Quickbooks that deserve consideration. I personally found QB the most intuitive and the best match for my own needs.For larger companies or ones with more complex needs (especially around inventories), owners often consider Peachtree, Sage, or other high-cost, high-feature solutions.I hope this is helpful!