I heard the word buffer after a long time today and wondering if somebody can give a good overview of buffer and some examples of how it matters in today's world.
A buffer is generally a portion of memory that contains data that has not yet been fully committed to its intended device. In the case of buffered I/O, generally there is a fast device and a slow device. The devices themselves need not have disparate speeds, but perhaps the interfaces between them differ or perhaps it is more time-consuming to either produce or consume the data than the other part is.
The idea is that you temporarily store the generated data in a buffer so that it is not lost when the slower device isn't ready to handle it. Once the device is ready, the another buffer may take the current buffer's place and the consuming device will process the data in the first buffer.
In this manner, the slower device receives the data at a moderated pace rather than the fire-hose that the original data source can be.
Related
I'm developing a C++ application in the ESP32-DevKitC board where I sense acceleration from an accelerometer. The application goal is to store the accelerometer data until storage is full and then send all the data through WiFi and start all again. The micro also goes to deep-sleep mode when is possible.
I'm currently using the ESP32 NVS library which is very well documented and pretty easy to use. The negative side of this is that the library uses Flash memory, therefore a lot of writings will end up degrading the drive.
I know that Espressif also offers some other storage libraries (FAT, SPIFFS, etc.) but, as far as I know (correct me if I'm wrong), they all use Flash drive.
Is there any other possibility of doing what I want to but without using the Flash storage?
Aclarations
Using Flash memory is not the problem itself, but degrading it.
Storage has to be non volatile or at least not being erased when the micro goes to deep-sleep mode.
I'm not using any Arduino library.
That's a great question that I wish more people would ask.
ESP32s use NOR flash storage, which is usually rated for between 10,000 to 100,000 write cycles (100,000 seems to be the standard these days). Flash can't write single bytes; instead of writes a "page" of bytes, which I believe is 256 bytes. So each 256 byte page is rated for at least 100,000 cycles. When a device is rated for 100,000 cycles it's likely to be usable for at least 10 times that, but the manufacturer is not going to make any promises beyond the 100,000.
SPIFFS (and LittleFS, now used on the ESP8266 Arduino Core) perform "wear leveling", to minimize the number of times a particular page is written. So if you modify the same section of a file repeatedly, it will automatically be written to different pages of flash. FAT is not designed to work well with flash storage; I would avoid it.
Whether SPIFFS with wear leveling will be adequate for your needs depends on your needed lifetime of the device versus how much data you'll be writing and how frequently.
NVS may perform some level of wear levelling, to an extent I'm unsure about. Here, in a forum post with 2 ESP employees, they both confirm that NVS does do some form of wear levelling. NVS is best used to persist things like configuration information that doesn't change frequently. It's not a great choice for storing information that's updated often.
You mentioned that the data just needs to survive deep sleep. If that's the case, your best option (if it's large enough) is to use the ESP32's RTC static RAM. This chunk of memory will survive restarts and deep sleep mode, but will lose its state if power is interrupted. It's real RAM so you won't wear it out by writing to it frequently, and it doesn't cost a lot of energy to write to. The catch is there's only 8KB of it.
If the 8KB of RTC RAM isn't enough and you're writing too much data too frequently to trust that SPIFFS will be okay, your best bet would be an SD card. The ESP32 can talk to an SD card adapter. SD cards use NAND flash, which has a much greater lifespan than NOR and can be safely overwritten many more times (which is why these kinds of cards are usable for filesystems in devices like Raspberry Pis).
Writing to flash also takes much more energy than writing to regular RAM. If your device is going to be battery powered, the RTC RAM is also a better choice than SPIFFS or an SD card from a power savings perspective.
Finally, if you use the RTC RAM I'd recommend starting to write it over wifi before it's full, as bringing up wifi and transmitting the data could easily take long enough that you might run out of space for some samples. Using it as a ring buffer and starting the transmit process when you hit a high water mark rather than when the buffer is full would probably be your best bet.
I know i'm late with this answer but you can buy ESP32 modules with external RAM even with 4-8mb. External ram is really fast ( at least much faster than the flash, it uses SPI interface to communicate ) and you can fit a lot of sensor readings in there.
I'm using an ESP32_WROVER_E module with 8mb external ram ( 4mb is usable with normal function calls ) and 16mb flash.
Here is a link of the module that i'm using at TME's site.
can someone tell me which is the page write buffer of this memory fram MB85RC256V
is it 32Kbyte ?
This device doesn't have a page write buffer: it is capable of writing individual bytes as fast as you can send them, so no buffering is needed.
Buffer size is something you have to worry about on much slower memory devices, such as EEPROM, that need many milliseconds to do an erase/write cycle. Devices with a write buffer are capable of writing multiple bytes in that same time - but it's entirely your responsibility to make sure that all the bytes fit in the same page. Crossing a page boundary in the middle of a write is likely to result in some data being written to the wrong address.
I have an AVX2 implementation of some workload.
I have determined that the vast majority of the execution time is occupied
by the memory loads and stores.
In an attempt to improve performance, I tried to change the conventional stores
to streaming (non-temporal) stores.
However, this change had little to no positive performance impact (I was expecting a sizeable performance increase).
What could be the reason for this?
The use of streaming stores can lead to a better performance under some circumstances:
The data "to be stored" is not read before writing: Streaming stores are write-through, which produces immediate bus traffic. The standard store uses a write back strategy which may delay the bus operation until a later time and avoids bus operations with multiple writes to the same cache line.
The time used for stores is smaller than the time used for calculation: A streaming store has to be finished before the next streaming store can be issued. Thus, ahving too liitle computation in between two streaming stores leads to some idle time for the processor in which no further computation can be executed. Where this problem may also be possible with standard stores, streaming stores even increase it.
The data "to be stored" is not needed shortly after being written: The streaming store surpasses caches while writing/storing. Thus, there is no copy of the data in the cache. When reading the data aftwerwards the data has to be loaded into the cache. Thus, you have no gain over a standard store. However, when using a standard store, the data is loaded into the cache, modified there, and maybe still there when a later access happens.
So you have to consider your code and problem, to these circumstances to know if streaming stores are worth a try. In an unfitting scenario your performance might even drop.
A blog entry with additional info and a benchmark can be found e.g. here.
I'm trying to troubleshoot drops in FPS. I see that Metal Flushes are what takes up most of the rendering time. Is that a good thing?
I am not sure about this, since Apple does not seem to have documented what exactly a "Metal Flush" is anywhere, but I'll answer based on previous experience with OpenGL:
During the execution cycle of a GPU-powered application, the CPU will push data to the GPU, wait for the GPU to finish operating on this data (possibly doing other work in the meantime), and as soon as the GPU is done, push more data and request more operations. Typically, "flushing" would mean that the CPU is waiting on the GPU to finish operations ("flushing out old data") so that it can push more data to the GPU.
So, if my interpretation is correct, that would mean that "Metal flush" measures the time the CPU spends waiting on video memory to free up so it can push more data and request operations to the GPU. In that case, it could be a good thing or a bad thing:
There will always be some communication overhead between the CPU and the GPU, so if most of your rendering time is being taken up by "Metal Flush", it might mean that your application is just running fast enough that most of the delay between frames is just communications overhead. In that case, it would be a good thing.
On the other hand, you might be pushing a lot of data to the GPU and the time needed to copy the data and process it might be causing delays. In that case, it would be a bad thing.
In the end, the important thing here is to ensure your FPS is consistently high. If your FPS is dropping due to "Metal Flush", you might want to try to space out your data transfers - for instance, storing textures in chunks and/or using lower resolution textures would probably help with that.
In my application I need to read data from an input stream. I have set the current buffer size for reading as 1024. But I have seen in some Android applications buffer size has been kept as 8192 (8 KB). Will there be any specific advantage if I increase the buffer size in my application to 8KB?
Any expert opinion will be much appreciated.
Edit: (I am using BB OS 6 and 7 and I am dealing with network inputstream.)
I can't say that I've found the universally best buffer size, but it seems to me that something in the range of 1KB to 8KB should be fine in most situations (for BlackBerry Java apps).
Keep in mind that if the amount of data is small (so you'd probably only need one or two buffers at 1KB-8KB), it's probably best just to use the IOUtilities method:
byte[] result = IOUtilities.streamToBytes(inputStream);
with which you don't need to actually pick a buffer size. But, if you know that result would be a large block of data, you're probably right in wanting to read one buffer at a time.
However, I would argue that the answer should almost always be obtained simply by building the app, and measuring performance with a few different values for byte buffer size. It's easy enough to change one constant, build, run and measure again, and then you're not guessing, or taking the advice of someone who doesn't know all the details of your app.
See here for information about BlackBerry Eclipse plugin memory analysis, and
here for BlackBerry Eclipse plugin profiling.
These tools are found in Eclipse by selecting the Window menu, then Show View -> Other... -> BlackBerry -> BlackBerry Memory Statistics View, or BlackBerry Profiler View, while debugging.
This way, you can see how much memory, or processor, the network code is using during the call to retrieve data and populate your buffer.
More
BlackBerry InputStream to String conversion
This question was also asked in the official BlackBerry forum here:
http://supportforums.blackberry.com/t5/Java-Development/What-is-the-best-size-for-a-buffer-in-BlackBerry/td-p/2559417
The OP gave this clarification:
"I am reading from network. Once I establish socket connection with the server, the server will send me notifications one after the other. I need to read the notifications/data from the inputstream available in the socket connection. For this I have a background thread which checks anything is available in the inputstream and if something is available, it will read with the help of a buffer and then passes the read data to a StringBuffer."
Given this information, I have a different take, in that I think the BlackBerry network handling abstracts the Java application from the network buffer processing to the extent that the application buffer size will have little if any impact on the performance.
But be aware, this is only my opinion.
My response on that thread was as follows:
First thing to note is that the method "isAvailable()", in my experience, does not work correctly on OS 5.0 and earlier. It is fixed in OS 6 (at least from my testing).
Because isAvailable() was broken, (and for other application reasons) what I have implemented for a socket connection is that each message is preceded by a length. So in the socket connection, I read the length of the next message, and then the actual data. This is done with no blocking - in other words I read the entire message, regardless of size. I recommend you do the same. The message must exist in full somewhere so it makes no difference if it is in some memory managed by the socket connection, or in some memory managed by you.
Note also, until OS 6.0, when you did the read you would get all the data to fill the buffer you had - in other words it waited till the buffer was full. In OS 6.0 and later, the read can complete without giving you a full buffer.
In your case, you might be working in a post OS 6.0 only, so you could use isAvailable() - create a buffer of that size, and read everything. I can't see that it makes any difference whether you have the bytes in memory managed by the socket, or memory managed by you.
But in fact, I would argue that the best approach is the one that makes your processing simplest. So for example, if you know that the next message is 200 bytes, then read 200 bytes, and then process that message. Then read the next message.
You could spend a lot of time attempting to manage the buffers to match the underlying socket buffers. I don't know exactly how the underlying BlackBerry socket processing code works, but it doesn't put data directly into your buffers. So let it manage its buffer size to optimize the network, you manage your buffer size to optimize your processing. That will work best for everyone.